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Inceptive Mind","url":"https://news.google.com/rss/articles/CBMiiwFBVV95cUxQZEc1emRWYmlXS2hSQjZjZ3hfWkczNlFsUDZKRkg2cFhIbElxOFBKNVQyQ2xrT0tQYTF3X0RrVmVLcjhFTVliNE9QZ3FZYXpXbDZrdVRsSG9SaEY2alZEcHg5cnRKTkpPN2tMUXJGY1ZBNGZ4ZFE3SlpLTVJmblU5TF8wNGdTelJaM3RJ?oc=5","publisher":"Inceptive Mind","date":"2026-09-20","snippet":"AMD’s Venice CPUs Bring 256 Cores to Agentic AI Inceptive Mind"}],"search_interest_index":null,"search_interest_trend":null,"wikipedia_monthly_views":null,"hn_mention_count":null,"hn_top_stories":[],"wayback_first_year":null,"sec_incorporation_state":null,"sec_latest_filing_type":null,"sec_latest_filing_date":null,"sec_filings":[],"research_papers_count":null,"research_citations_count":null,"research_h_index":null,"research_topics":[],"is_federal_contractor":null,"earnings_calendar":[],"industry_canonical":null,"enrichment_sources":[],"last_enriched_at":null},"hiring":{"total_jobs":8,"categories":[{"category":"engineering","count":4},{"category":"it","count":3},{"category":"sales","count":1}],"experience_levels":[{"level":"senior","count":5},{"level":"mid","count":1},{"level":"entry","count":1}],"work_arrangements":[{"arrangement":"onsite","count":4},{"arrangement":"hybrid","count":4}],"top_titles":[{"title":"Secure Data Infrastructure for AI","count":1},{"title":"Open Apply","count":1},{"title":"High-throughput data generation to advance ML design","count":1},{"title":"Foundation and generative models for biomolecules","count":1},{"title":"Data Generation for ML-based molecule design","count":1},{"title":"Characterizing biological foundation models","count":1},{"title":"Advancing Inceptive's commercial strategy","count":1},{"title":"Accelerating impact through partnerships","count":1}],"locations":[{"location":"palo alto, ca","count":4},{"location":"palo alto, berlin, or zurich","count":1},{"location":"palo alto","count":1},{"location":"berlin, germany or palo alto, ca or zurich, switzerland","count":1},{"location":"berlin","count":1}],"skills":[{"skill":"Python","required":4,"preferred":0,"total":4},{"skill":"Machine Learning","required":3,"preferred":0,"total":3},{"skill":"Deep Learning","required":2,"preferred":0,"total":2},{"skill":"Computational Biology","required":2,"preferred":0,"total":2},{"skill":"Biostatistics","required":1,"preferred":1,"total":2},{"skill":"Biologics","required":1,"preferred":0,"total":1},{"skill":"Genetic Medicines","required":1,"preferred":0,"total":1},{"skill":"Deep Learning Methods","required":1,"preferred":0,"total":1},{"skill":"Business Development","required":1,"preferred":0,"total":1},{"skill":"Pharma","required":1,"preferred":0,"total":1},{"skill":"Biotech","required":1,"preferred":0,"total":1},{"skill":"VC","required":1,"preferred":0,"total":1},{"skill":"Market Research","required":0,"preferred":1,"total":1},{"skill":"Networking","required":0,"preferred":1,"total":1},{"skill":"Relationship Building","required":0,"preferred":1,"total":1},{"skill":"Pipeline Management","required":0,"preferred":1,"total":1},{"skill":"Deal Execution","required":0,"preferred":1,"total":1},{"skill":"Negotiations","required":0,"preferred":1,"total":1},{"skill":"Diligence","required":0,"preferred":1,"total":1},{"skill":"Closing","required":0,"preferred":1,"total":1}],"salary_stats":{"count":7,"min":172500,"q1":187500,"median":187500,"q3":237500,"max":237500},"job_types":[{"type":"full-time","count":8}],"latest_jobs":[{"id":"job_d31b352b-d11","title":"Data Generation for ML-based molecule design","source_url":"https://job-boards.greenhouse.io/inceptive/jobs/5182394007","location":"Palo Alto, CA","job_type":"full-time","experience_level":"senior","work_arrangement":"hybrid","category":"IT","description":"<p>At Inceptive, you will help pioneer the next generation of AI-designed drugs, with the potential to positively impact billions of people, as part of a collaborative, antedisciplinary team.</p>\n<p>We advance the state of the art in molecular design by training large-scale foundation models that enable cutting-edge generative approaches. Those models depend on rich, high-quality experimental data that captures biological function. Progress requires not only building better models, but also designing better experiments, understanding measurement systems, and generating datasets that faithfully represent underlying biology.</p>\n<p>You will collaborate closely with biologists and machine learning researchers to design, analyze, and improve the experiments that power our models. You will help determine what data should be generated, how experiments should be structured, how measurement artifacts can be identified, and how biological insights can be translated into scalable data generation strategies.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Embody our vision of an antedisciplinary environment and embrace learning about areas outside of your traditional area of expertise</li>\n<li>Develop statistical and computational approaches to characterize assay quality, reproducibility, and sources of experimental variation</li>\n<li>Identify and investigate sources of bias and measurement artifacts in biological datasets</li>\n<li>Design and analyze large-scale biological experiments that generate training and evaluation data for machine learning models</li>\n<li>Partner with experimental scientists to improve assay design, controls, and data collection strategies</li>\n<li>Collaborate with machine learning researchers to understand how experimental design decisions impact model training and evaluation</li>\n<li>Analyze, visualize, and communicate findings to support decision-making across scientific and engineering teams</li>\n</ul>\n<p>Qualifications:</p>\n<ul>\n<li>PhD in computational biology, systems biology, genomics, bioengineering, biostatistics, biophysics, or a related quantitative discipline, or equivalent practical experience</li>\n<li>Demonstrated track record of analyzing complex biological datasets and translating computational insights into experimental validation or new data collection</li>\n<li>Strong foundation in experimental design, statistical analysis, and quantitative reasoning</li>\n<li>Deep understanding of sources of experimental variability, batch effects, and assay artifacts in biological data</li>\n<li>Capable programmer in Python and common scientific computing libraries</li>\n<li>Excellent written and verbal communication skills, including the ability to communicate effectively across computational and experimental disciplines</li>\n<li>Availability to work with team members across US and Europe, with meetings starting at 8am PT and ending at 7pm CET</li>\n<li>Readiness to travel several times a year for company retreats and business events</li>\n</ul>\n<p>Preferred technical skills:</p>\n<ul>\n<li>3+ years of post-PhD experience in computational biology, biostatistics, or a related field</li>\n<li>Experience connecting experimental outcomes to machine learning model development and evaluation</li>\n</ul>\n<p>Compensation: $135K – $240K + Bonus + Equity</p>\n<p>Benefits:</p>\n<ul>\n<li>Competitive compensation package</li>\n<li>30 days paid vacation per year</li>\n<li>Comprehensive health insurance for US-based employees</li>\n<li>401K with company match for US-based employees and Direktversicherung for German employees</li>\n<li>Quarterly company-wide retreats</li>\n<li>Monthly wellness benefit</li>\n<li>Budget for multiple visits per year to our offices in Berlin, Palo Alto or Switzerland</li>\n<li>Learning &amp; Development budget to attend conferences, take courses, or otherwise invest in your professional growth, as well as access to the Learning &amp; Development platform EdX and Hone</li>\n</ul>","enriched_at":1784300633763},{"id":"job_b4edc821-b29","title":"Characterizing biological foundation models","source_url":"https://job-boards.greenhouse.io/inceptive/jobs/5182395007","location":"Palo Alto, CA","job_type":"full-time","experience_level":"senior","work_arrangement":"hybrid","category":"IT","description":"<p>At Inceptive, you will help pioneer the next generation of AI-designed drugs, with the potential to positively impact billions of people, as part of a collaborative, antedisciplinary team.</p>\n<p>We advance the state of the art in molecular design by training large-scale foundation models that enable cutting-edge generative approaches. Those models learn from diverse biological datasets and are refined through focused experimentation, large-scale training, and feedback from lab measurements.</p>\n<p>Progress depends not only on building better models, but also on understanding what they learn, where they fail, how data shapes their behavior, and how to evaluate them against biologically meaningful objectives.</p>\n<p>You will collaborate closely with AI researchers and biologists to rigorously characterize the behavior, capabilities, and limitations of biological foundation models and their applications. You will identify valuable datasets, develop meaningful evaluations, investigate model behavior, and generate insights that guide model development, data strategy, and experimental priorities across the company.</p>\n<p>Your Mission, should you choose to accept it:</p>\n<ul>\n<li>Embody our vision of an antedisciplinary environment and embrace learning about areas outside of your traditional area of expertise</li>\n<li>Investigate how model performance changes with data quantity, data quality, dataset composition, and training methodology</li>\n<li>Develop biologically meaningful evaluations and benchmarks that measure progress toward therapeutic design objectives</li>\n<li>Design and execute rigorous experiments to understand the behavior, capabilities, and limitations of biological foundation models</li>\n<li>Identify sources of potential artifacts, bias, and noise in biological datasets</li>\n<li>Identify promising biological datasets for model training and evaluation, and develop computational pipelines for preprocessing, quality control, and exploratory analysis</li>\n<li>Design studies, in silico or in the lab, that reveal what models have learned and which biological signals drive model behavior</li>\n<li>Work with biologists to formulate hypotheses and translate biological questions into measurable machine learning experiments</li>\n<li>Partner with AI researchers and engineers to prioritize research directions, data collection efforts, and model improvements</li>\n<li>Analyze, visualize, and communicate experimental findings to inform decisions across teams</li>\n</ul>\n<p>Qualifications:</p>\n<ul>\n<li>PhD in computational biology, statistics, physics, machine learning, or a related quantitative discipline, or equivalent practical experience, with record of publications or open source tooling in these fields</li>\n<li>Strong quantitative reasoning and statistical intuition</li>\n<li>Demonstrated ability to identify important scientific questions, design rigorous investigations, and draw reliable conclusions from complex biological data</li>\n<li>Experience analyzing high throughput sequencing data (e.g. RNA-seq, functional genomics / transcriptomics, MPRA), with a focus on robust statistical analysis</li>\n<li>Experience collaborating closely with AI/machine learning researchers or applying machine learning or generative AI tools to scientific problems</li>\n<li>Familiarity with current AI/machine learning methods, including generative foundation models, representation learning, and model evaluation</li>\n<li>Familiarity with publicly available biological datasets and data derived from high throughput assays</li>\n<li>Capable programmer in Python and common scientific computing libraries</li>\n<li>Excellent written and verbal communication skills, including the ability to explain complex findings to audiences with diverse technical backgrounds</li>\n<li>Availability to work with team members across US and Europe, with meetings starting at 8am PT and ending at 7pm CET</li>\n<li>Readiness to travel several times a year for company retreats and business events</li>\n</ul>\n<p>Preferred technical skills:</p>\n<ul>\n<li>3+ years of post-PhD experience in computational biology, biostatistics, machine learning research, or a related field</li>\n</ul>\n<p>What we offer:</p>\n<ul>\n<li>A competitive compensation package</li>\n<li>30 days paid vacation per year</li>\n<li>Comprehensive health insurance for US based employees</li>\n<li>401K with company match for US based employees and Direktversicherung for German employees</li>\n<li>Quarterly company-wide retreats</li>\n<li>Monthly wellness benefit</li>\n<li>Budget for multiple visits per year to our offices in Berlin, Palo Alto or Switzerland</li>\n<li>Learning &amp; Development budget to attend conferences, take courses, or otherwise invest in your professional growth, as well as access to the Learning &amp; Development platform EdX and Hone</li>\n</ul>","enriched_at":1784300576993},{"id":"job_6859ec73-4b2","title":"Secure Data Infrastructure for AI","source_url":"https://job-boards.greenhouse.io/inceptive/jobs/5167437007","location":"Berlin","job_type":"full-time","experience_level":"senior","work_arrangement":"hybrid","category":"IT","description":"<p>At Inceptive, you will drive forward development that could help billions of people. You will be part of a collaborative, antedisciplinary team building biological software.</p>\n<p>Our AI models depend on rich, high-quality biological datasets. The integrity, security, and reliability of those datasets and of the infrastructure that supports them are critical to everything we do. As we scale, we need someone who can architect and own the systems that keep our data and our customer&#39;s data safe, well-governed, and optimally accessible to our machine learning pipelines. This is a senior, hands-on role: you will design and build, not just advise.</p>\n<p>You will work closely with our ML researchers, data engineers, and computational biologists to understand data flows end to end. This includes data ingestion, training, inference, analysis, logging, result output, and model serving.</p>\n<p>Your work will help secure our infrastructure at every stage. It will also protect our most sensitive assets, including model configurations and weights, training data, and experimental results, from external adversaries and insider threats.</p>\n<h3>Your Mission, should you choose to accept it</h3>\n<ul>\n<li>Embody our vision of an antedisciplinary environment and embrace learning about areas outside of your traditional area of expertise</li>\n<li>Architect, implement, and own secure data infrastructure supporting our AI model training and deployment pipelines , from raw data ingestion to model weight storage and access</li>\n<li>Build and operate foundational security services: authentication systems, access brokers, secrets management, key management platforms, and egress/ingress controls across our multi-cloud environment</li>\n<li>Design and enforce data governance frameworks, such as RBAC/ABAC policies, audit logging, encryption at rest and in transit, workload identity, and data lifecycle management</li>\n<li>Embed security directly into our MLOps pipeline: CI/CD security controls, container and Kubernetes security, namespace isolation, and pod security standards</li>\n<li>Conduct threat modeling and secure design reviews for existing and new systems, proactively identifying attack surfaces across the full AI tech stack</li>\n<li>Identify, prioritize, and drive remediation of vulnerabilities across our data systems, cloud environments, and ML tooling, including AI-specific risks like data poisoning, model extraction, and unauthorized access to model weights</li>\n<li>Build detection and alerting pipelines for anomalous data access patterns and potential exfiltration events</li>\n<li>Establish security best practices and educate team members on secure coding, infrastructure patterns, and secure data handling for AI systems</li>\n<li>Partner with ML and biology teams to ensure data handling practices meet the highest standards for sensitive research data</li>\n</ul>\n<h3>Qualifications and Requirements</h3>\n<ul>\n<li>7+ years of hands-on experience in data engineering, infrastructure security, or software security, ideally spanning both disciplines</li>\n<li>Strong System and Software Engineering skills with production-quality code in Python, Bash, and at least one systems programming language (Go, Rust, or C++)</li>\n<li>Deep experience securing GCP cloud environments, including IAM, VPC design, secrets management, workload authentication, and cloud security posture management</li>\n<li>Proven track record designing and implementing identity and access management systems, including credential issuance, rotation, and least-privilege enforcement at scale</li>\n<li>Hands-on experience with Kubernetes security: RBAC policies, namespace isolation, workload identity, pod security</li>\n<li>Certifications (Highly Desirable): CISSP, OSCP, or GWAPT for core security credentialing, plus AI-focused certifications such as GAISC, Offensive ML (OffSec), or cloud provider AI security tracks (AWS/GCP).</li>\n<li>Availability to work with team members across US and Europe, with meetings starting at 8am PT and ending at 7pm CET</li>\n<li>Readiness to travel several times a year for company retreats and business events</li>\n<li>We value the benefits of in-person collaboration and expect candidates to primarily work from our Palo Alto or Berlin offices</li>\n</ul>\n<h3>Preferred Technical Skills</h3>\n<ul>\n<li>PhD or advanced degree in Computer Science, Electrical Engineering, or a related field or equivalent practical experience</li>\n<li>Familiarity with AI/ML-specific security risks: data poisoning, model extraction, prompt injection, unauthorized model weight access, and adversarial attacks on training pipelines, and practical mitigations for each</li>\n<li>Experience securing ML infrastructure, including model registries, training cluster access, dataset versioning, experiment tracking systems, and GPU compute environments</li>\n<li>Proficiency with Terraform infrastructure-as-code and GitOps security practices, including automated misconfiguration detection and remediation</li>\n<li>Experience with compliance frameworks relevant to sensitive research data (SOC 2, HIPAA, GDPR) and translating them into concrete engineering controls</li>\n<li>Background in offensive security techniques, including threat modeling, penetration testing, vulnerability research, or red team exercises. In a nutshell, the ability to think like an adversary</li>\n<li>Experience building detection pipelines for insider threats, data exfiltration, and anomalous access patterns</li>\n<li>Knowledge of cryptographic protocols and their practical application in distributed systems (key management, TLS, secure enclaves)</li>\n<li>Prior experience in a fast-moving startup or research environment where security must scale alongside rapid growth</li>\n</ul>\n<h3>Compensation</h3>\n<p>$200K – $275K + Bonus + Equity</p>\n<h3>What we offer</h3>\n<ul>\n<li>A competitive compensation package</li>\n<li>30 days paid vacation per year</li>\n<li>Comprehensive health insurance for US based Beginners</li>\n<li>401K with company match for US based Beginners and Direktversicherung for German Beginners</li>\n<li>Quarterly company-wide retreats</li>\n<li>Monthly wellness benefit</li>\n<li>Budget for multiple visits per year to our offices in Berlin, Palo Alto or Switzerland</li>\n<li>Learning &amp; Development budget to attend conferences, take courses, or otherwise invest in your professional growth, as well as access to the Learning &amp; Development platform EdX and Hone</li>\n<li>A buddy to help you get settled</li>\n</ul>","enriched_at":1781789896718},{"id":"job_01d6483b-e80","title":"Accelerating impact through partnerships","source_url":"https://job-boards.greenhouse.io/inceptive/jobs/5155248007","location":"Palo Alto, CA","job_type":"full-time","experience_level":"senior","work_arrangement":"onsite","category":"Engineering","description":"<p>At Inceptive, you will drive development forward that could help billions of people. To accomplish this, you will be part of a collaborative, interdisciplinary team building our biological software.</p>\n<p>We are looking for an exceptional and motivated individual to join our business development team.</p>\n<p>You will be joining a dynamic and agile team, set to execute on our mission and capitalize on scientific, business, and strategic opportunities. We are seeking an Alliance Manager to lead and grow our strategic partnerships in oligonucleotide therapeutics, with a primary focus on small interfering RNA (siRNA) drug discovery. As a key member of our Business Development team, you will serve as the primary interface between our company and our external partners , spanning pharmaceutical companies, academic institutions, and technology providers , ensuring alliances are structured for scientific success and commercial value.</p>\n<p>This role sits at the intersection of cutting-edge AI-driven biology and next-generation RNA therapeutics. You will leverage our proprietary AI platform to identify, establish, and manage high-impact collaborations that accelerate the development of siRNA-based medicines.</p>\n<h3>Responsibilities</h3>\n<ul>\n<li>Embody our vision of an interdisciplinary environment and embrace learning about areas outside of your traditional area of expertise</li>\n</ul>\n<ul>\n<li>Serve as the primary point of contact for existing siRNA and oligonucleotide partnerships, managing day-to-day alliance operations and escalation pathways</li>\n</ul>\n<ul>\n<li>Establish and lead Joint Steering Committees (JSCs), Joint Research Committees (JRCs), and other governance bodies, preparing agendas, minutes, and action tracking</li>\n</ul>\n<ul>\n<li>Monitor contractual milestones, deliverables, and timelines; proactively identify and resolve issues that could jeopardize partnership success</li>\n</ul>\n<ul>\n<li>Coordinate cross-functional internal teams (Biology, Chemistry, AI/ML, Regulatory, Legal, Finance) to fulfill partner obligations and advance shared programs</li>\n</ul>\n<ul>\n<li>Drive successful execution of partnered programs against scientific and operational milestones and enable expansion opportunities across strategic partnerships</li>\n</ul>\n<ul>\n<li>Prepare documents and presentations to senior management to help drive decision-making through the deal process</li>\n</ul>\n<ul>\n<li>Travel to industry events, scientific or business-oriented</li>\n</ul>\n<h3>Scientific &amp; Strategic Engagement</h3>\n<ul>\n<li>Develop a deep understanding of partner pipelines, strategic priorities, and siRNA platform capabilities to align collaboration goals</li>\n</ul>\n<ul>\n<li>Translate AI platform outputs and siRNA design insights into compelling partnership narratives for both scientific and business audiences</li>\n</ul>\n<ul>\n<li>Collaborate with internal discovery teams to ensure partner-facing scientific deliverables meet alliance commitments</li>\n</ul>\n<ul>\n<li>Stay current on competitive landscape in RNAi therapeutics, GalNAc-siRNA conjugates, lipid nanoparticle (LNP) delivery, and AI-driven target discovery</li>\n</ul>\n<h3>Qualifications</h3>\n<ul>\n<li>Ph.D. or M.S. in Molecular Biology, Biochemistry, Pharmacology, or a related life sciences field; MBA a plus</li>\n</ul>\n<ul>\n<li>5+ years of experience in alliance management, business development, or strategic partnerships within the biopharmaceutical or biotech industry</li>\n</ul>\n<ul>\n<li>Working knowledge of oligonucleotide therapeutics , particularly siRNA biology, mechanism of action, and drug development challenges</li>\n</ul>\n<ul>\n<li>Demonstrated experience managing complex, multi-party research or licensing collaborations from initiation through program delivery</li>\n</ul>\n<ul>\n<li>Exceptional interpersonal, negotiation, and communication skills; ability to influence without direct authority across internal and external stakeholders</li>\n</ul>\n<ul>\n<li>Strong project management skills with proficiency in tools such as Smartsheet, Asana, or equivalent platforms</li>\n</ul>\n<ul>\n<li>Familiarity with AI/ML applications in drug discovery, including sequence-based target identification or predictive ADME/toxicity modeling</li>\n</ul>\n<ul>\n<li>Prior experience negotiating term sheets, CDAs, MTAs, or master research collaboration agreements</li>\n</ul>\n<ul>\n<li>Existing network within the oligonucleotide therapeutics ecosystem (pharma, biotech, CRO, and academic partners)</li>\n</ul>\n<ul>\n<li>Availability to accommodate working with team members across different time zones, with one or two meetings per week starting at 8am PT or finishing at 7pm CET</li>\n</ul>\n<ul>\n<li>Readiness to travel several times a year for company retreats and business events</li>\n</ul>\n<ul>\n<li>We value the benefits of in-person collaboration and expect candidates to primarily work at our office locations</li>\n</ul>\n<p>Compensation</p>\n<p>$135K – $240K + Bonus + Equity</p>\n<p>What we offer</p>\n<ul>\n<li>A competitive compensation package</li>\n</ul>\n<ul>\n<li>30 days paid vacation per year</li>\n</ul>\n<ul>\n<li>Comprehensive health insurance for US based Beginners</li>\n</ul>\n<ul>\n<li>401K with company match for US based Beginners and Direktversicherung for German Beginners</li>\n</ul>\n<ul>\n<li>Quarterly company-wide retreats</li>\n</ul>\n<ul>\n<li>Monthly wellness benefit</li>\n</ul>\n<ul>\n<li>Budget for multiple visits per year to our offices in Berlin, Palo Alto or Switzerland</li>\n</ul>\n<ul>\n<li>Learning &amp; Development budget to attend conferences, take courses, or otherwise invest in your professional growth, as well as access to the Learning &amp; Development platform EdX and Hone</li>\n</ul>\n<ul>\n<li>A buddy to help you get settled</li>\n</ul>\n<p>*Varies by country and does not apply to internships</p>\n<p>At Inceptive, we are creating tools to develop increasingly powerful biological software for the rational design of novel, broadly accessible medicines and biotechnologies previously out of reach. Our team brings together vast expertise in molecular biology, machine learning, and software engineering, and we are all working towards becoming interdisciplinary, meaning we deepen the knowledge we have in our area of expertise while also expanding our knowledge of completely new fields.</p>\n<p>We approach our goals with a Beginner&#39;s mind, humbly and with fresh eyes, and aim to become the pioneers of a new discipline rooted in biology as much as in deep learning, whose impact will be realized together with out-of-the-box thinkers in business and entrepreneurship, defying established categorizations. We are building a company culture centered around growth, learning, and discovery. We believe in humility and open-mindedness in how we approach each other, as well as problems we don&#39;t yet have solutions for.</p>","enriched_at":1780582100563},{"id":"job_030d0558-4cf","title":"Open Apply","source_url":"https://job-boards.greenhouse.io/inceptive/jobs/4085997007","location":"Palo Alto, Berlin, or Zurich","job_type":"full-time","experience_level":"entry","work_arrangement":"hybrid","category":"Engineering","description":"<p>At Inceptive, you will drive research forward that could help billions of people. As part of a collaborative, interdisciplinary team building our biological software, you will work alongside scientists, deep learning researchers, engineers, and entrepreneurs.</p>\n<p>To accomplish this, you will be available to accommodate working with team members across different time zones, with one or two meetings per week starting at 8am PT or finishing at 7pm CET. You will also be ready to travel several times a year for company retreats and business events.</p>\n<p>We value the benefits of in-person collaboration and prefer candidates who can easily and regularly connect at one of our office locations.</p>\n<p>As a member of our team, you will receive a competitive compensation package, including $105K – $240K + Bonus + Equity. You will also enjoy 30 days paid vacation per year, comprehensive health insurance for US-based beginners, and a 401K with company match for US-based beginners and Direktversicherung for German beginners.</p>\n<p>Additionally, you will participate in quarterly company-wide retreats, monthly wellness benefits, and budget for multiple visits per year to our offices in Berlin, Palo Alto, or Switzerland. You will also have access to the Learning &amp; Development platform EdX and Hone, as well as a buddy to help you get settled.</p>\n<p>Our team brings together vast expertise in molecular biology, machine learning, and software engineering, and we are all working towards becoming interdisciplinary, meaning we deepen the knowledge we have in our area of expertise while also expanding our knowledge of completely new fields.</p>\n<p>We approach our goals with a beginner&#39;s mind, humbly and with fresh eyes, and aim to become the pioneers of a new discipline rooted in biology as much as in deep learning, whose impact will be realized together with out-of-the-box thinkers in business and entrepreneurship, defying established categorizations.</p>\n<p>We are building a company culture centered around growth, learning, and discovery. We believe in humility and open-mindedness in how we approach each other, as well as problems we don&#39;t yet have solutions for.</p>","enriched_at":1776527784003},{"id":"job_bf1d2cbb-e48","title":"High-throughput data generation to advance ML design","source_url":"https://job-boards.greenhouse.io/inceptive/jobs/4951550007","location":"Palo Alto, CA","job_type":"full-time","experience_level":"senior","work_arrangement":"onsite","category":"Engineering","description":"<p>At Inceptive, you will drive development forward that could help billions of people. To accomplish this, you will be part of a collaborative, interdisciplinary team building our biological software.</p>\n<p>Our AI models learn to generate therapeutic molecules with improved properties by training on natural and experimentally-derived data. Acquiring data relevant to function at scale is a critical step in maximizing the performance of our models. We think broadly about the type and scale of data necessary to improve our models, then identify or invent the methods needed to acquire that data.</p>\n<p>You will be responsible for the development and deployment of novel high-throughput assays to measure various properties of large sequence libraries. You will use a data-driven approach to optimize assays and apply chemical and biological insights to maximize the utility of information collected. You will apply this data to efficiently improve design of therapeutic molecules in close collaboration with biologists, ML and data engineers, and translational experts.</p>\n<h3>Responsibilities</h3>\n<ul>\n<li>Embody our vision of an interdisciplinary environment and embrace learning about areas outside of your traditional area of expertise</li>\n</ul>\n<ul>\n<li>Collaborate with team members from diverse backgrounds to create experiments that creatively leverage biology and computation</li>\n</ul>\n<ul>\n<li>Develop and execute pooled assays to measure sequence-to-function in vitro, in cells, and in vivo</li>\n</ul>\n<ul>\n<li>Generate, analyze, and communicate data that maximally impacts AI-based molecular design</li>\n</ul>\n<h3>Qualifications</h3>\n<ul>\n<li>PhD and 4+ years of post-PhD experience (e.g., startup, industry, or research)</li>\n</ul>\n<ul>\n<li>Problem-solver who combines deep knowledge of experimental methods with quantitative intuition to generate biological data at and beyond the state-of-the-art</li>\n</ul>\n<ul>\n<li>Solid foundation in theory and techniques of molecular and cellular biology</li>\n</ul>\n<ul>\n<li>History of building highly multiplexed assays to generate rich datasets from mammalian cells, such as large functional screens or single-cell &#39;omics</li>\n</ul>\n<ul>\n<li>Scientific programming (preferably in Python), including analysis and visualization of complex data</li>\n</ul>\n<ul>\n<li>Availability to work with team members across US and Europe, with meetings starting at 8am PT</li>\n</ul>\n<ul>\n<li>Readiness to travel several times a year for company retreats and business events</li>\n</ul>\n<ul>\n<li>We value in-person collaboration and expect candidates to work at our lab location</li>\n</ul>\n<h3>Preferred skills</h3>\n<ul>\n<li>Experience with mammalian synthetic biology, particularly for cell therapy applications</li>\n</ul>\n<ul>\n<li>Knowledge of RNA biology, biochemistry, and biologics drug development</li>\n</ul>\n<ul>\n<li>Strong understanding of next-generation sequencing platforms (Illumina, Oxford Nanopore, Pac Bio), including library preparation and data analysis</li>\n</ul>\n<ul>\n<li>Experience generating and analyzing large &#39;omics datasets, via sequencing and/or mass spectrometry</li>\n</ul>\n<p>Compensation</p>\n<p>$135K – $240K + Bonus + Equity</p>\n<p>What we offer</p>\n<ul>\n<li>A competitive compensation package</li>\n</ul>\n<ul>\n<li>30 days paid vacation per year</li>\n</ul>\n<ul>\n<li>Comprehensive health insurance for US based Beginners</li>\n</ul>\n<ul>\n<li>401K with company match for US based Beginners and Direktversicherung for German Beginners</li>\n</ul>\n<ul>\n<li>Quarterly company-wide retreats</li>\n</ul>\n<ul>\n<li>Monthly wellness benefit</li>\n</ul>\n<ul>\n<li>Budget for multiple visits per year to our offices in Berlin, Palo Alto or Switzerland</li>\n</ul>\n<ul>\n<li>Learning &amp; Development budget to attend conferences, take courses, or otherwise invest in your professional growth, as well as access to the Learning &amp; Development platform EdX and Hone</li>\n</ul>\n<ul>\n<li>A buddy to help you get settled</li>\n</ul>\n<p>*Varies by country and does not apply to internships</p>","enriched_at":1776527696135},{"id":"job_f0792575-799","title":"Advancing Inceptive's commercial strategy","source_url":"https://job-boards.greenhouse.io/inceptive/jobs/4934419007","location":"Palo Alto","job_type":"full-time","experience_level":"mid","work_arrangement":"onsite","category":"Sales","description":"<p>We are seeking a Business Development professional to help identify, structure, and execute strategic partnerships at the intersection of science, strategy, and dealmaking. As part of our collaborative, antedisciplinary team, you will drive development forward that could help billions of people.</p>\n<p>Your mission will be to embody our vision of an antedisciplinary environment and embrace learning about areas outside of your traditional area of expertise. You will identify and source new business opportunities with biotech and pharma through market research, networking, and by building business relationships to expand Inceptive’s network.</p>\n<p>Key responsibilities include leading outbound BD efforts, including prospecting, relationship building, and pipeline management, as well as supporting deal execution (term sheets, negotiations, diligence, closing) and collaborating with scientific and technical teams to translate platform capabilities into partner value.</p>\n<p>To succeed in this role, you will need a Master&#39;s in science (PhD preferred), ideally with a background in biologics, genetic medicines, or deep learning methods applied to drug development, and 3 years of experience in business development in pharma, biotech or VC.</p>\n<p>The salary range for this position is $135K – $240K + Bonus + Equity.</p>","enriched_at":1776527626861},{"id":"job_19c6b9e4-ff6","title":"Foundation and generative models for biomolecules","source_url":"https://job-boards.greenhouse.io/inceptive/jobs/4961579007","location":"Berlin, Germany or Palo Alto, CA or Zurich, Switzerland","job_type":"full-time","experience_level":null,"work_arrangement":"onsite","category":"Engineering","description":"<p>At Inceptive, you will drive forward development that could help billions of people. You will be part of a collaborative, interdisciplinary team building our biological software.</p>\n<p>The design space of biomolecules is unimaginably vast , far beyond what can be explored experimentally. Yet within this space lie molecules with properties essential for new medicines. Our machine learning models learn to design therapeutic biomolecules with specific, desirable functions.</p>\n<p>We advance the state of the art in molecular design by training large-scale foundation models and developing cutting-edge generative approaches. The models learn from diverse heterogeneous datasets and are refined through focused fine-tuning and feedback from experiments. Key to progress is a team that combines exceptional machine learning expertise with thorough domain understanding.</p>\n<p>You will collaborate closely with other machine learning researchers and engineers, as well as computational and experimental biologists, to advance these models and translate their capabilities into real therapeutic designs.</p>\n<h4>Responsibilities</h4>\n<ul>\n<li>Embody our vision of an interdisciplinary environment and embrace learning about areas outside of your traditional area of expertise</li>\n</ul>\n<ul>\n<li>Develop, implement, train, and iteratively improve state-of-the-art models for biomolecule design</li>\n</ul>\n<ul>\n<li>Analyze, visualize, and communicate results to support team efforts in improving models and data</li>\n</ul>\n<ul>\n<li>Create, deploy, and refine tools for efficient, reliable machine learning experimentation and production</li>\n</ul>\n<ul>\n<li>Work with biologists to collect data for the training and evaluation of generative models of biomolecules</li>\n</ul>\n<ul>\n<li>Provide mentorship and technical direction to team members as appropriate</li>\n</ul>\n<h4>Qualifications</h4>\n<ul>\n<li>3+ years of hands-on experience developing ML models</li>\n</ul>\n<ul>\n<li>Demonstrated track record of implementing, training, improving advanced machine learning models</li>\n</ul>\n<ul>\n<li>Highly capable programmer fluent in Python ecosystem and PyTorch or similar deep learning framework</li>\n</ul>\n<ul>\n<li>Availability to work with team members across US and Europe, with meetings starting at 8am PT and ending at 7pm CET</li>\n</ul>\n<ul>\n<li>Readiness to travel several times a year for company retreats and business events</li>\n</ul>\n<h4>Compensation</h4>\n<p>$200K – $275K + Bonus + Equity</p>\n<h4>Benefits</h4>\n<ul>\n<li>A competitive compensation package</li>\n</ul>\n<ul>\n<li>30 days paid vacation per year</li>\n</ul>\n<ul>\n<li>Comprehensive health insurance for US based employees</li>\n</ul>\n<ul>\n<li>401K with company match for US based employees and Direktversicherung for German employees</li>\n</ul>\n<ul>\n<li>Quarterly company-wide retreats</li>\n</ul>\n<ul>\n<li>Monthly wellness benefit</li>\n</ul>\n<ul>\n<li>Budget for multiple visits per year to our offices in Berlin, Palo Alto or Switzerland</li>\n</ul>\n<ul>\n<li>Learning &amp; Development budget to attend conferences, take courses, or otherwise invest in your professional growth, as well as access to the Learning &amp; Development platform EdX and Hone</li>\n</ul>\n<ul>\n<li>A buddy to help you get settled</li>\n</ul>\n<p>At Inceptive, we are creating tools to develop increasingly powerful biological software for the rational design of novel, broadly accessible medicines and biotechnologies previously out of reach. Our team brings together vast expertise in molecular biology, machine learning, and software engineering, and we are all working towards becoming interdisciplinary, meaning we deepen the knowledge we have in our area of expertise while also expanding our knowledge of completely new fields.</p>","enriched_at":1776527541853}],"category_normalised":[{"category":"engineering","count":4},{"category":"it","count":3},{"category":"sales","count":1}],"velocity":{"weeks":[{"week_start":"2026-06-01","count":1},{"week_start":"2026-06-15","count":1},{"week_start":"2026-07-13","count":2}],"trend":"stable","wow_pct":100},"momentum":{"recent_14d":0,"prior_14d":0,"growth_pct":0,"classification":"stable"},"salary_vs_industry":{"company_median":187500,"industry_median":null,"percentile":null,"sample_size":3,"by_region":[{"region":"United States","company_median":187500,"industry_median":null,"sample":2}],"transparency_pct":38,"industry_transparency_pct":0,"transparency_warning":false},"market_share":{"company_jobs":8,"industry_total":8,"share_pct":100,"rank":1,"peer_count":1},"ai_exposure":null,"peer_set":[],"skills_lq":[],"geographic_shift":{"current":[{"region":"United States","count":6,"share_pct":75},{"region":"EU","count":2,"share_pct":25}],"emerging":[],"shrinking":[]},"seniority_anomalies":{"exec_recent_30d":0,"exec_prior_90d_avg":0,"exec_growth_pct":0,"notable_exec_hires":[]},"posting_dynamics":{"median_days_open":null,"industry_median_days_open":null,"long_open_count":8,"closure_rate_pct":100}}}}