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HPCwire","url":"https://news.google.com/rss/articles/CBMi_AFBVV95cUxNTzNxOTQ3cmFieWhxeXdEN01aazBWeWQzemhScFlCRmQ5WXlGN0xyNXRsVDZ2RV9NNlN0aEZiQjFkQVEtcGhRZHZCMnFhV1hWcmNpUjE4Y1BqUE1BeGRId0xHblU3bHBmLU41MC00YXdOanEtS0x5dEpybTFhNTZSeEx3NmlEOHNtejJoSTRtb205dWtONUc4cXRWTC1SLVNCMGVBZUxOMTRUdTMwcExQWFdOSlE1WHpyQW1YN0RJcS1wVXFENHluT3RqbkFFemxGSmVTSFhhQ0lONTRsUF9SSEhiNUVoalg3VU03a0FpbG9ZSUUwY3pIT0IyOFM?oc=5","publisher":"HPCwire","date":"2026-09-09","snippet":"Labelbox Introduces LLM Solution to Help Enterprises Innovate with Generative AI, Expands Partnership with Google Cloud HPCwire"},{"title":"Snorkel AI Alternatives & Competitors (2026) - GetLatka","url":"https://news.google.com/rss/articles/CBMiY0FVX3lxTFBWVGdLNTVTRm00bkZzWG16OFNBQ2thb0dBU0c3OHFvaWFDeDlYUkU2Slk5OGJyLXdITE1ockNJR0pzck56YVJQRUMwVTBHOTVjOE9LVzZhQXkxb3ItVDJhdkVMQQ?oc=5","publisher":"GetLatka","date":"2026-09-10","snippet":"Snorkel AI Alternatives & Competitors (2026) GetLatka"},{"title":"Top 10: Data Labelling Tools - AI Magazine","url":"https://news.google.com/rss/articles/CBMie0FVX3lxTFBNaW0xUWZxek5FNG1lOU1tRy1MMFhoWlY5SjdGTkYwRk9QbThPUmtLQVN5cE1kTEhsTVFuSVJwTUp3RXpRSFhKV3J4aFpJbWREWGQ5amNsWUpJSGZhSmNiQmtPdkxyUHdLS2xyclRfYzJFN0ZKSmZ0MU5uZw?oc=5","publisher":"AI Magazine","date":"2026-09-16","snippet":"Top 10: Data Labelling Tools AI Magazine"}],"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":5,"categories":[{"category":"engineering","count":4},{"category":"human resources","count":1}],"experience_levels":[{"level":"senior","count":3},{"level":"staff","count":1}],"work_arrangements":[{"arrangement":"hybrid","count":2},{"arrangement":"remote","count":1},{"arrangement":"onsite","count":1}],"top_titles":[{"title":"Staff ML Engineer, Agent Training & Environments","count":1},{"title":"Member of Technical Staff","count":1},{"title":"Global Specialized Domain Expert Recruiter (Contractor)","count":1},{"title":"Forward Deployed Engineering Manager","count":1},{"title":"Deployment Lead","count":1}],"locations":[{"location":"san francisco, ca","count":1},{"location":"san francisco bay area, ca","count":1},{"location":"san francisco bay area","count":1},{"location":"san francisco","count":1},{"location":"remote, united states","count":1}],"skills":[{"skill":"Machine Learning","required":2,"preferred":0,"total":2},{"skill":"Data Pipelines","required":2,"preferred":0,"total":2},{"skill":"Python","required":2,"preferred":0,"total":2},{"skill":"Reinforcement Learning","required":1,"preferred":1,"total":2},{"skill":"Technical Program Management","required":1,"preferred":0,"total":1},{"skill":"Customer Relationship Management","required":1,"preferred":0,"total":1},{"skill":"Operational And Financial Execution","required":1,"preferred":0,"total":1},{"skill":"Data-centric Approaches","required":1,"preferred":0,"total":1},{"skill":"AI Development","required":1,"preferred":0,"total":1},{"skill":"RL/evaluation","required":1,"preferred":0,"total":1},{"skill":"Technical Leadership","required":1,"preferred":0,"total":1},{"skill":"People Management","required":1,"preferred":0,"total":1},{"skill":"Technical Depth","required":1,"preferred":0,"total":1},{"skill":"Delivery Quality","required":1,"preferred":0,"total":1},{"skill":"Quality Instrumentation","required":1,"preferred":0,"total":1},{"skill":"Instruction Writing","required":1,"preferred":0,"total":1},{"skill":"Customer-facing Presentation","required":1,"preferred":0,"total":1},{"skill":"RLHF","required":0,"preferred":1,"total":1},{"skill":"Reinforcement-learning Environments","required":0,"preferred":1,"total":1},{"skill":"Evaluation/benchmark Work","required":0,"preferred":1,"total":1}],"salary_stats":null,"job_types":[{"type":"full-time","count":4},{"type":"contract","count":1}],"latest_jobs":[{"id":"job_e378eca6-6ab","title":"Member of Technical Staff","source_url":"https://job-boards.greenhouse.io/labelbox/jobs/5246362007","location":"San Francisco Bay Area","job_type":"full-time","experience_level":"senior","work_arrangement":null,"category":"Engineering","description":"<h3>Shape the Future of AI</h3>\n<p>At Labelbox, we&#39;re building critical infrastructure for breakthrough AI models at leading research labs and enterprises. Since 2018, we&#39;ve pioneered data-centric approaches fundamental to AI development.</p>\n<h3>The Role</h3>\n<p>We&#39;re hiring a Member of Technical Staff to design, develop, and produce Frontier Data Products. You&#39;ll build sandboxed, reproducible environments AI agents rely on during training and evaluation.</p>\n<h3>What You&#39;ll Do</h3>\n<ul>\n<li>Design, build, and maintain sandboxed RL environments for agentic AI training</li>\n<li>Develop reproducible, containerized execution environments</li>\n<li>Integrate with and extend open-source agentic tooling and custom CLI/API harnesses</li>\n<li>Build instrumentation and observability layers</li>\n<li>Collaborate with data operations to design task curricula and evaluation protocols</li>\n<li>Own environment deployment and reliability</li>\n<li>Rapidly prototype new environment types</li>\n</ul>\n<h3>What We&#39;re Looking For</h3>\n<ul>\n<li>2+ years of professional software engineering experience with strong fundamentals in Python and at least one systems-level language</li>\n<li>Demonstrated experience with containerization and sandboxing</li>\n<li>Familiarity with RL concepts</li>\n<li>Experience building or maintaining developer tooling, CLI tools, or infrastructure automation</li>\n<li>Comfort working with browser automation frameworks or terminal interaction tooling</li>\n<li>Strong debugging instincts</li>\n<li>Ability to read and implement from academic papers and open-source benchmark repositories</li>\n</ul>\n<h3>Why This Role Matters</h3>\n<ul>\n<li>Reinforcement learning has become the state-of-the-art approach for training agentic AI, and environment quality is one of its biggest bottlenecks</li>\n<li>You&#39;ll work across a portfolio of projects spanning different AI labs and model capabilities</li>\n<li>Alignerr is a small, high-impact team inside Labelbox with startup-level ownership and growth-stage resources</li>\n</ul>\n<h3>Life at Labelbox</h3>\n<ul>\n<li>Fast-paced and high-intensity environment</li>\n<li>Career advancement opportunities directly tied to your impact</li>\n<li>Be part of building the foundation for humanity&#39;s most transformative technology</li>\n</ul>","enriched_at":1790121905800},{"id":"job_f4bfc8de-4b8","title":"Global Specialized Domain Expert Recruiter (Contractor)","source_url":"https://job-boards.greenhouse.io/labelbox/jobs/5211972007","location":"Remote, United States","job_type":"contract","experience_level":null,"work_arrangement":"remote","category":"Human Resources","description":"<h3>Shape the Future of AI</h3>\n<p>At Labelbox, we&#39;re building the critical infrastructure that powers breakthrough AI models at leading research labs and enterprises. Since 2018, we&#39;ve been pioneering data-centric approaches that are fundamental to AI development, and our work becomes even more essential as AI capabilities expand exponentially.</p>\n<h3>About Labelbox</h3>\n<p>We&#39;re the only company offering three integrated solutions for frontier AI development:</p>\n<ul>\n<li>Enterprise Platform &amp; Tools: Advanced annotation tools, workflow automation, and quality control systems that enable teams to produce high-quality training data at scale</li>\n<li>Frontier Data Labeling Service: Specialized data labeling through Alignerr, leveraging subject matter experts for next-generation AI models</li>\n<li>Expert Marketplace: Connecting AI teams with highly skilled annotators and domain experts for flexible scaling</li>\n</ul>\n<h3>Why Join Us</h3>\n<ul>\n<li>High-Impact Environment: We operate like an early-stage startup, focusing on impact over process. You&#39;ll take on expanded responsibilities quickly, with career growth directly tied to your contributions.</li>\n<li>Technical Excellence: Work at the cutting edge of AI development, collaborating with industry leaders and shaping the future of artificial intelligence.</li>\n<li>Innovation at Speed: We celebrate those who take ownership, move fast, and deliver impact. Our environment rewards high agency and rapid execution.</li>\n<li>Continuous Growth: Every role requires continuous learning and evolution. You&#39;ll be surrounded by curious minds solving complex problems at the frontier of AI.</li>\n<li>Clear Ownership: You&#39;ll know exactly what you&#39;re responsible for and have the autonomy to execute. We empower people to drive results through clear ownership and metrics.</li>\n</ul>\n<h3>About the role</h3>\n<p>What if your recruiting expertise could help connect the world&#39;s leading experts to some of today&#39;s most advanced technology initiatives?</p>\n<p>Labelbox powers Alignerr, a network of world-class subject matter experts who contribute their expertise to help develop, evaluate, and improve cutting-edge AI systems. We&#39;re looking for driven outbound recruiters to identify and engage highly specialized professionals for our highest-priority projects.</p>\n<p>Your mission is to find exceptional domain experts (PhDs, researchers, academics, and senior industry practitioners) in fields like scientific computing, cybersecurity, finance, engineering, mathematics, and other specialized disciplines. These experts apply their knowledge to create high-quality evaluations, verification tasks, and domain-specific training environments that improve the capabilities of next-generation AI models.</p>\n<p>This isn&#39;t volume recruiting. It&#39;s precision hunting for the best minds in the world, on behalf of the projects that matter most. And you&#39;re paid for outcomes: every placement earns you a commission, with no ceiling on what you can make.</p>\n<h3>What you&#39;ll own</h3>\n<ul>\n<li>Run targeted outbound sourcing campaigns to identify and engage hard-to-reach subject matter experts.</li>\n<li>Recruit specialists across priority domains including scientific computing, cybersecurity, quantitative finance, engineering, mathematics, healthcare, legal, and other highly technical fields.</li>\n<li>Source PhDs, researchers, professors, and experienced industry professionals with deep domain expertise.</li>\n<li>Build and manage pipelines of niche, high-caliber experts for ongoing and future projects.</li>\n<li>Assess candidates for technical depth, professional accomplishments, and communication skills.</li>\n<li>Clearly communicate opportunities and build relationships with busy senior professionals.</li>\n<li>Guide candidates efficiently through the recruiting process from initial outreach to successful placement.</li>\n<li>Work independently in a fully remote, asynchronous environment on your own schedule.</li>\n</ul>\n<h3>Who you are</h3>\n<ul>\n<li>Proven experience in recruiting, sourcing, talent acquisition</li>\n<li>Skilled at outbound sourcing through LinkedIn, academic institutions, research communities, professional associations, GitHub, conferences, and other niche networks.</li>\n<li>Comfortable identifying and engaging senior-level professionals, including PhDs, researchers, faculty, and industry experts.</li>\n<li>Self-motivated, organized, and driven by performance-based compensation.</li>\n<li>Excellent written communication skills with the ability to engage professionals across cultures and time zones.</li>\n<li>Based in Latin America, Mexico, Europe, or a comparable region and able to work fully remotely.</li>\n<li>No prior AI recruiting experience required, we&#39;ll provide the context you need.</li>\n</ul>\n<h3>Signals you’ll stand out</h3>\n<ul>\n<li>Experience recruiting research, academic, scientific, engineering, healthcare, legal, cybersecurity, quantitative finance, or other specialized talent.</li>\n<li>Demonstrated success sourcing PhDs, researchers, or other difficult-to-reach expert populations.</li>\n<li>Experience working in agency recruiting, executive search, or commission-based recruiting environments.</li>\n<li>Some familiarity with AI, reinforcement learning, or data annotation workflows is helpful but not required.</li>\n</ul>\n<h3>Why join us</h3>\n<ul>\n<li>Uncapped, performance-based earnings with commission for every successful placement.</li>\n<li>Flexible, fully remote work with complete control over your schedule.</li>\n<li>Recruit world-class experts whose knowledge helps advance cutting-edge AI technology.</li>\n<li>Access a consistent pipeline of specialized recruiting opportunities across diverse technical disciplines.</li>\n<li>Join a long-term opportunity with a rapidly growing organization as Alignerr continues to expand.</li>\n</ul>","enriched_at":1786690945648},{"id":"job_2327bed9-ab4","title":"Staff ML Engineer, Agent Training & Environments","source_url":"https://job-boards.greenhouse.io/labelbox/jobs/5199053007","location":"San Francisco","job_type":"full-time","experience_level":"staff","work_arrangement":"hybrid","category":"Engineering","description":"<h3>Shape the Future of AI</h3>\n<p>At Labelbox, we&#39;re building critical infrastructure for breakthrough AI models at leading research labs and enterprises. Since 2018, we&#39;ve pioneered data-centric approaches fundamental to AI development.</p>\n<h3>Role Overview</h3>\n<p>Labelbox is the RL data factory for advancing frontier agent capabilities. We build the data, environments, and evaluations that frontier labs use to train and judge their agents.</p>\n<p>This role sits where training meets infrastructure. You will run experiments and build systems that run them: environments agents act in, verifiers that decide whether they succeeded, and fine-tuning pipelines that turn that signal into a better model.</p>\n<h3>Responsibilities</h3>\n<ul>\n<li>Develop RL environments for agentic tasks, including task definitions, tool surfaces, state and reset semantics, reward design, and the harness that runs thousands of them in parallel.</li>\n<li>Create verifiers and graders, such as programmatic checks, LLM judges, rubric pipelines, and pass@k scoring.</li>\n<li>Design fine-tuning pipelines that turn evaluation signals into measurable agent improvements , SFT and RL, from data collection through training to checkpoint evaluation.</li>\n<li>Build eval systems that run millions of agent trajectories to measure model and product quality.</li>\n<li>Develop training and serving infrastructure that scales to the throughput frontier labs need: multi-launcher orchestration, long-running job fault tolerance, cost accounting.</li>\n</ul>\n<h3>Requirements</h3>\n<p>As an engineer:</p>\n<ul>\n<li>A 3+ year track record of shipping systems that customers and other engineers rely on.</li>\n<li>Exceptional throughput without sacrificing quality.</li>\n<li>Strong system and API design judgment.</li>\n<li>Daily experience with coding agents and shipping production code.</li>\n<li>Deep proficiency in Python and comfort across the rest of the stack.</li>\n</ul>\n<p>As an RL post-training practitioner:</p>\n<ul>\n<li>Experience fine-tuning models for agentic tasks and making them measurably better.</li>\n<li>Built environments agents operate in, with expertise in reward and task design.</li>\n<li>Designed verifiers or graders for open-ended work.</li>\n<li>Debugging training runs forensically and methodically.</li>\n<li>Understanding of compute economics.</li>\n</ul>\n<h3>Nice to Have</h3>\n<ul>\n<li>Experience with agent harnesses and coding agents as subjects of training and evaluation.</li>\n<li>Knowledge of multi-tenancy and isolation for untrusted agent execution.</li>\n<li>Background in production distributed systems, ML infrastructure, or data systems at scale.</li>\n<li>Experience working directly with frontier labs or highly technical customers.</li>\n</ul>\n<h3>Benefits</h3>\n<ul>\n<li>High-impact environment with expanded responsibilities and career growth tied to contributions.</li>\n<li>Technical excellence and collaboration with industry leaders.</li>\n<li>Innovation at speed with ownership and rapid execution.</li>\n<li>Continuous growth and learning with curious minds.</li>\n<li>Clear ownership and autonomy to execute.</li>\n</ul>\n<h3>Compensation</h3>\n<ul>\n<li>Expected annual base salary range: $250,000-$280,000 USD.</li>\n</ul>\n<h3>Life at Labelbox</h3>\n<ul>\n<li>Location: San Francisco.</li>\n<li>Work style: Hybrid model with 3 days per week in office.</li>\n<li>Environment: Fast-paced and high-intensity.</li>\n<li>Growth: Career advancement opportunities directly tied to impact.</li>\n</ul>","enriched_at":1785373610467},{"id":"job_c762f40f-828","title":"Deployment Lead","source_url":"https://job-boards.greenhouse.io/labelbox/jobs/5158994007","location":"San Francisco, CA","job_type":"full-time","experience_level":"senior","work_arrangement":"onsite","category":"Engineering","description":"<h3>Shape the Future of AI</h3>\n<p>At Labelbox, we&#39;re building the critical infrastructure that powers breakthrough AI models at leading research labs and enterprises. Since 2018, we&#39;ve been pioneering data-centric approaches that are fundamental to AI development, and our work becomes even more essential as AI capabilities expand exponentially.</p>\n<h3>About Labelbox</h3>\n<p>We&#39;re the only company offering three integrated solutions for frontier AI development:</p>\n<ul>\n<li>Enterprise Platform &amp; Tools: Advanced annotation tools, workflow automation, and quality control systems that enable teams to produce high-quality training data at scale</li>\n</ul>\n<ul>\n<li>Frontier Data Labeling Service: Specialized data labeling through Alignerr, leveraging subject matter experts for next-generation AI models</li>\n</ul>\n<ul>\n<li>Expert Marketplace: Connecting AI teams with highly skilled annotators and domain experts for flexible scaling</li>\n</ul>\n<h3>Why Join Us</h3>\n<ul>\n<li>High-Impact Environment: We operate like an early-stage startup, focusing on impact over process. You&#39;ll take on expanded responsibilities quickly, with career growth directly tied to your contributions.</li>\n</ul>\n<ul>\n<li>Technical Excellence: Work at the cutting edge of AI development, collaborating with industry leaders and shaping the future of artificial intelligence.</li>\n</ul>\n<ul>\n<li>Innovation at Speed: We celebrate those who take ownership, move fast, and deliver impact. Our environment rewards high agency and rapid execution.</li>\n</ul>\n<ul>\n<li>Continuous Growth: Every role requires continuous learning and evolution. You&#39;ll be surrounded by curious minds solving complex problems at the frontier of AI.</li>\n</ul>\n<ul>\n<li>Clear Ownership: You&#39;ll know exactly what you&#39;re responsible for and have the autonomy to execute. We empower people to drive results through clear ownership and metrics.</li>\n</ul>\n<h3>Role Overview</h3>\n<p>Get an inside look and hear directly from our current Forward Deployed Engineers here!</p>\n<p>About the Role</p>\n<p>The Deployment Lead owns the successful delivery of complex customer programs from initial scoping through steady-state execution , on time, to the quality bar, and at margin. This is a senior, customer-facing role for operators who can translate a customer&#39;s technical and business requirements into clear execution plans, coordinate multiple internal workstreams, own the economics of the deployment, and ensure projects meet their throughput, quality, delivery, and margin commitments.</p>\n<p>Deployment Leads sit at the intersection of customer relationship management, technical program management, and operational and financial execution. They must understand the underlying technical requirements of each program well enough to pressure-test implementation plans and communicate tradeoffs clearly with the customer , and own the unit economics well enough to protect margin while they do it.</p>\n<p>The Deployment Lead is the operations-and-margin leg of the customer team: they own delivery and the deployment&#39;s economics, partnering with the General Manager, who owns the broader customer relationship and growth. They are the primary point of accountability for the delivery of a major customer or portfolio of projects, and the customer&#39;s point of contact when timelines, requirements, or operational performance are in play. They coordinate Technical Program Managers and Forward Deployed Engineers across the account, ensuring each workstream is staffed from the pools, technically sound, and aligned with the broader customer objective.</p>\n<p>This role is equivalent in seniority to a TPM Manager, but with a stronger emphasis on customer ownership, deployment success, and margin. It is a senior destination on the TPM track and a pathway toward a General Manager role. General Managers own the broader account end-to-end, including the overall customer and researcher relationships, proposal development, account strategy, operating cadence, and the portfolio of deployments delivered for that customer.</p>\n<h3>What You&#39;ll Do</h3>\n<ul>\n<li>Own the end-to-end deployment of projects for one or more major customers, from initial scoping and technical design through launch and ongoing execution , accountable for throughput, quality, delivery, and margin.</li>\n</ul>\n<ul>\n<li>Own the economics of your deployments: instrument margin live, manage the cost-to-revenue picture across the account&#39;s projects, and make the in-flight calls (comp structure, staffing, project structure) that protect it, the level where TPMs escalate margin-structure decisions.</li>\n</ul>\n<ul>\n<li>Serve as the customer&#39;s primary point of contact for delivery , timelines, technical requirements, risks, and operational performance.</li>\n</ul>\n<ul>\n<li>Develop a detailed understanding of each customer&#39;s technical requirements: system constraints, integrations, data flows, workflows, and acceptance criteria.</li>\n</ul>\n<ul>\n<li>Translate customer requirements into clear project plans, milestones, owners, success metrics, and a margin model.</li>\n</ul>\n<ul>\n<li>Ensure the account&#39;s projects move through their gates , calibration before scaling, staged ramp, delivery acceptance , so quality and margin hold across the portfolio.</li>\n</ul>\n<ul>\n<li>Work closely with FDEs, TPMs, and FDRs to validate implementation plans, manage dependencies, and ensure technical decisions support the customer&#39;s goals and the deployment&#39;s economics.</li>\n</ul>\n<ul>\n<li>Coordinate TPMs and FDEs across multiple concurrent projects, maintaining a clear view of progress, staffing, risk, margin, and cross-project dependencies , and ensure projects are staffed from the pools and the data-trainer workforce is sized and productive via TPMs and Pod Leads.</li>\n</ul>\n<ul>\n<li>Communicate technical and economic tradeoffs and implementation risks clearly to customer stakeholders and internal teams.</li>\n</ul>\n<ul>\n<li>Identify risks early, establish mitigation plans, and escalate when timelines, technical feasibility, quality, or margin are at risk.</li>\n</ul>\n<ul>\n<li>Partner with FDEs, FDRs, the Talent/Crowd team, the GM, and platform teams to unblock execution.</li>\n</ul>\n<ul>\n<li>Establish the operating cadence, dashboards, and escalation paths that create visibility and accountability , and improve deployment playbooks as the organization scales.</li>\n</ul>\n<h3>What You&#39;ll Own</h3>\n<ul>\n<li>Delivery of your customer&#39;s portfolio , on time, to the quality bar, and at or above target margin.</li>\n</ul>\n<ul>\n<li>The deployment&#39;s economics: live margin, the cost-to-revenue picture, and the in-flight decisions that protect it.</li>\n</ul>\n<ul>\n<li>The customer&#39;s trust on delivery and operational performance.</li>\n</ul>\n<ul>\n<li>A clear operating cadence and a live view of progress, staffing, risk, and margin across projects.</li>\n</ul>\n<h3>What We&#39;re Looking For</h3>\n<ul>\n<li>Significant experience owning complex, cross-functional programs in a customer-facing environment , as an operator who has run things, not advised on them.</li>\n</ul>\n<ul>\n<li>Financial and commercial numeracy: comfort owning margin, building and reading the unit economics of a program, and making the call to protect it.</li>\n</ul>\n<ul>\n<li>Strong technical fluency and the ability to quickly understand complex systems, workflows, and implementation requirements.</li>\n</ul>\n<ul>\n<li>Ability to communicate credibly with technical customer stakeholders while translating technical detail into clear decisions for non-technical audiences.</li>\n</ul>\n<ul>\n<li>A track record of partnering effectively with engineers, program managers, and cross-functional operators.</li>\n</ul>\n<ul>\n<li>Excellent judgment: you can distinguish technical issues from execution issues from customer-management issues, and find the right path to resolution.</li>\n</ul>\n<ul>\n<li>A strong track record of delivering against ambitious timelines while holding a high bar for quality.</li>\n</ul>\n<ul>\n<li>Comfort operating in ambiguous environments where requirements evolve and processes are still being built.</li>\n</ul>\n<ul>\n<li>Strong operational instincts, a bias toward action, and attention to detail across multiple projects at once.</li>\n</ul>\n<h3>Nice to Have</h3>\n<ul>\n<li>Background in consulting, banking, private equity/VC, or an operating role where you owned a P&amp;L or a hard number.</li>\n</ul>\n<ul>\n<li>Experience deploying technical products, services, or data-intensive programs.</li>\n</ul>\n<ul>\n<li>Familiarity with AI, machine learning, data pipelines, or RL/evaluation</li>\n</ul>","enriched_at":1781035619704},{"id":"job_2d4b13c2-1b4","title":"Forward Deployed Engineering Manager","source_url":"https://job-boards.greenhouse.io/labelbox/jobs/5158989007","location":"San Francisco Bay Area, CA","job_type":"full-time","experience_level":"senior","work_arrangement":"hybrid","category":"Engineering","description":"<h3>Shape the Future of AI</h3>\n<p>At Labelbox, we&#39;re building the critical infrastructure that powers breakthrough AI models at leading research labs and enterprises. Since 2018, we&#39;ve been pioneering data-centric approaches that are fundamental to AI development, and our work becomes even more essential as AI capabilities expand exponentially.</p>\n<h3>About Labelbox</h3>\n<p>We&#39;re the only company offering three integrated solutions for frontier AI development:</p>\n<ul>\n<li>Enterprise Platform &amp; Tools: Advanced annotation tools, workflow automation, and quality control systems that enable teams to produce high-quality training data at scale</li>\n</ul>\n<ul>\n<li>Frontier Data Labeling Service: Specialized data labeling through Alignerr, leveraging subject matter experts for next-generation AI models</li>\n</ul>\n<ul>\n<li>Expert Marketplace: Connecting AI teams with highly skilled annotators and domain experts for flexible scaling</li>\n</ul>\n<h3>Why Join Us</h3>\n<ul>\n<li>High-Impact Environment: We operate like an early-stage startup, focusing on impact over process. You&#39;ll take on expanded responsibilities quickly, with career growth directly tied to your contributions.</li>\n</ul>\n<ul>\n<li>Technical Excellence: Work at the cutting edge of AI development, collaborating with industry leaders and shaping the future of artificial intelligence.</li>\n</ul>\n<ul>\n<li>Innovation at Speed: We celebrate those who take ownership, move fast, and deliver impact. Our environment rewards high agency and rapid execution.</li>\n</ul>\n<ul>\n<li>Continuous Growth: Every role requires continuous learning and evolution. You&#39;ll be surrounded by curious minds solving complex problems at the frontier of AI.</li>\n</ul>\n<ul>\n<li>Clear Ownership: You&#39;ll know exactly what you&#39;re responsible for and have the autonomy to execute. We empower people to drive results through clear ownership and metrics.</li>\n</ul>\n<h3>The role</h3>\n<p>The FDE Manager leads and grows the team of Forward Deployed Engineers who own the high-level technical side of our customer data programs. FDEs scope tasks, design the pipelines and measurement that turn a customer&#39;s goal into a training signal, write the instructions that guide Alignerrs, and work out what each customer actually needs from their data. The FDE Manager owns the people who do that work , their craft, their growth, and how they&#39;re deployed across domains and customers , and is accountable for the technical quality and consistency of what the team produces.</p>\n<p>This role sits at the intersection of people leadership, technical depth, and delivery quality. The FDE Manager must understand the technical substance of our projects well enough to coach on scoping and pipeline design, pressure-test instructions, judge whether a project&#39;s data will genuinely move the customer&#39;s model, and raise the bar on measuring quality early rather than late. It&#39;s a player-coach role: you lead people, but you stay close enough to the work to set and defend the craft bar yourself.</p>\n<p>The FDE Manager reports to the Services lead and partners closely with the SPL Manager, Deployment Leads, and General Managers. A core part of the role is keeping FDEs at the right altitude , focused on higher-level technical and customer-facing work , and actively handing the day-to-day running of projects to the SPLs and Pod Leads, so the team&#39;s most expensive technical talent is never absorbed into project operations.</p>\n<p>The FDE Manager also owns FDE onboarding and is the steward of the FDE career path, which runs from FDE to FDE 2 to FDE Manager, with branches toward the Forward Deployed Researcher (FDR) track and, in time, toward General Manager.</p>\n<h3>What You&#39;ll Do</h3>\n<ul>\n<li>Lead the FDE team end-to-end: hire, coach, manage performance, and develop careers across the FDE track and toward FDR or GM.</li>\n</ul>\n<ul>\n<li>Own the supply side of FDE staffing: commit FDEs to the staffing cadence and match them to projects by skill and development need, balancing each FDE&#39;s preferred vertical with where the work is, and staffing to the phase of a project rather than parking people for its full length.</li>\n</ul>\n<ul>\n<li>Set and uphold the craft bar: sharp task scoping, sound pipeline and measurement design (including the LLM-as-judge and quality instrumentation that surface problems early), clear instruction writing, and compelling customer-facing presentation of findings.</li>\n</ul>\n<ul>\n<li>Protect FDE focus: keep day-to-day project operations with the SPLs and Pod Leads, and keep FDEs on scoping, technical depth, and what the customer needs from the data.</li>\n</ul>\n<ul>\n<li>Own FDE onboarding and the bar that certifies a new FDE as ready to be staffed: define which projects are eligible to onboard on, maintain the instruction and Loom repository, and run the onboarding program , including the core exercise (read a past project&#39;s instructions, explain them back, and write a new version in the repo).</li>\n</ul>\n<ul>\n<li>Drive reuse and leverage: build the templates, tooling, and playbooks that stop FDEs rebuilding pipelines and instructions from scratch each project, so the team&#39;s capacity compounds as we scale.</li>\n</ul>\n<ul>\n<li>Ensure FDEs work hand-in-glove with FDRs on research, efficacy, and customer needs, and partner with whoever owns quality sign-off so quality is caught in flight, not at delivery.</li>\n</ul>\n<ul>\n<li>Partner with the SPL Manager, Deployment Leads, and GMs on staffing, delivery, and alignment with customer objectives.</li>\n</ul>\n<ul>\n<li>Step in on escalations when a pipeline, delivery, or customer relationship is at risk.</li>\n</ul>\n<ul>\n<li>Maintain a clear, live view of team capacity, utilization, and bench across active projects.</li>\n</ul>\n<h3>What You&#39;ll Own</h3>\n<ul>\n<li>The capability and craft bar of the FDE team.</li>\n</ul>\n<ul>\n<li>How quickly and consistently new FDEs reach a staffable standard.</li>\n</ul>\n<ul>\n<li>Healthy deployment , the right FDEs on the right projects, at the right altitude and utilization.</li>\n</ul>\n<ul>\n<li>A growing bench of FDEs developing toward FDR and future leadership.</li>\n</ul>\n<h3>What We&#39;re Looking For</h3>\n<ul>\n<li>A strong forward-deployed / FDE background, or significant experience managing technical or delivery people , and readiness to be a hands-on, player-coach manager.</li>\n</ul>\n<ul>\n<li>Strong technical fluency in our domain: enough depth in frontier-data work, RL environments, data pipelines, and quality/evaluation to coach credibly on scoping, pipelines, judge design, and data quality.</li>\n</ul>\n<ul>\n<li>Excellent judgment on what makes data genuinely useful to a customer , how to translate ambiguous requirements into clear plans, and how to tell whether data will actually move a model.</li>\n</ul>\n<ul>\n<li>A track record of developing people and giving direct, useful feedback.</li>\n</ul>\n<ul>\n<li>A high bar for quality paired with the ability to deliver against ambitious timelines.</li>\n</ul>\n<ul>\n<li>Comfort operating in ambiguous, fast-scaling environments where the processes are still being built.</li>\n</ul>\n<ul>\n<li>The ability to manage multiple people and projects at once without losing attention to detail.</li>\n</ul>\n<h3>Nice to Have</h3>\n<ul>\n<li>Direct experience with RLHF, reinforcement-learning environments, evaluation/benchmark work, or LLM-as-judge systems.</li>\n</ul>\n<ul>\n<li>Experience working with forward-deployed engineers, solutions engineers, or implementation teams.</li>\n</ul>\n<ul>\n<li>Experience building onboarding programs, instruction systems, or training content.</li>\n</ul>\n<ul>\n<li>Experience scaling a team and its operating processes in a high-growth environment.</li>\n</ul>\n<h3>What Success Looks Like</h3>\n<p>In your first several months, you&#39;ll take ownership of the FDE team, raise the bar on scoping, pipeline, and instruction quality, and get onboarding running smoothly , eligible projects defined, the instruction and Loom repository in good shape, and new FDEs reaching a staffable standard faster and more consistently. You&#39;ll build strong working relationships with the SPL Manager, Deployment Leads, and GMs, keep FDEs well-deployed and at the right altitude, and become the person the team relies on for craft and career growth.</p>\n<p>Over time, you&#39;ll define how FDEs work at scale: the templates, tooling, and playbooks that let the team produce more without rebuilding from scratch, a measurement-and-quality craft bar that surfaces problems early, and a pipeline of FDEs growing</p>","enriched_at":1781035420188}],"category_normalised":[{"category":"engineering","count":4},{"category":"human resources","count":1}],"velocity":{"weeks":[{"week_start":"2026-06-08","count":2},{"week_start":"2026-07-27","count":1},{"week_start":"2026-08-10","count":1},{"week_start":"2026-09-21","count":1}],"trend":"stable","wow_pct":0},"momentum":{"recent_14d":0,"prior_14d":0,"growth_pct":0,"classification":"stable"},"salary_vs_industry":{"company_median":200000,"industry_median":null,"percentile":null,"sample_size":3,"by_region":[{"region":"United States","company_median":232500,"industry_median":null,"sample":2}],"transparency_pct":60,"industry_transparency_pct":0,"transparency_warning":false},"market_share":{"company_jobs":5,"industry_total":5,"share_pct":100,"rank":1,"peer_count":1},"ai_exposure":{"occupation_weighted_score":0.374,"skill_weighted_score":0,"top_exposed_titles":[],"top_exposed_skills":[]},"peer_set":[],"skills_lq":[],"geographic_shift":{"current":[{"region":"United States","count":3,"share_pct":60},{"region":"Remote","count":1,"share_pct":20},{"region":"Unknown","count":1,"share_pct":20}],"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":95,"industry_median_days_open":null,"long_open_count":2,"closure_rate_pct":0}}}}