S

Snorkel AI

Builds training data and test environments for AI

Vice President – Head of Forward Deployed Engineering

Full-Time
$268.8k - $403k
Expert
San Francisco, CA, USA+1 moreMore locations: New York, NY, USA
Hybrid
Engineering ManagementEngineering Leadership

About the job

Requirements
  • At least 10 years of experience in software or machine learning engineering, including at least 5 years leading multiple teams as a manager of managers.
  • Experience scaling an engineering organization of approximately 100 engineers and owning team planning, strategy, and alignment with company needs.
  • A strong engineering background in software or machine learning engineering.
  • Experience building and shipping artificial intelligence and machine learning systems to production, with strong experience using automated verification to decide what is good enough to ship.
  • Deep technical fluency to conduct architecture reviews and propose meaningful design changes, including direct experience with large language model application stacks, agents, orchestration, and large language model-based pipelines.
  • Strong customer accountability: delivering what customers intend, not just the literal specification, and adapting as their needs change.
Responsibilities
  • Lead and scale the Forward Deployed Engineering organization by setting its vision, defining the operating model and organizational design, and aligning team plans and strategy with company priorities.
  • Drive hiring during hypergrowth, build a strong bench of engineering managers and tech leads, and maintain a high hiring bar as the organization scales to more than 100 engineers.
  • Coach and develop engineering managers and technical lead managers who run pods of Forward Deployed Engineers, helping them grow from single-project owners into leaders who identify and solve problems across the delivery organization.
  • Drive reuse across the organization by identifying patterns across bespoke deliveries, having Forward Deployed Engineering build initial versions, and partnering with Platform Engineering to scale solutions company-wide.
  • Set engineering standards for pipeline design, data evaluation and verification, delivery sign-off, and root cause analysis.
  • Establish Forward Deployed Engineering as the final point of control for delivery quality by defining quality bars, owning sign-off on every dataset shipped, and ensuring every customer requirement is verified.
  • Own pipeline cost and performance, including token and compute costs, throughput, and latency, and be accountable for the targets and forecasts delivered by the teams.
  • Stay involved in the architecture of the organization’s pipelines by reviewing designs, identifying weaknesses, and proposing changes that improve quality, cost, and reuse.
  • Plan and adjust capacity as priorities shift, rebalancing teams quickly while keeping delivery commitments intact.
Desired Qualifications
  • A background in machine learning infrastructure or data platforms is strongly preferred.

About the company

S

Snorkel AI

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Snorkel AI builds training datasets and simulated work environments for AI labs and companies developing models and software agents. Its data products combine expert demonstrations, scoring rules, and quality checks, while runnable environments let agents practice tasks such as coding or using business software. The company pairs domain specialists with its own data development technology to generate examples, evaluate model behavior, and refine weak areas through repeated feedback. Customers buy ready-made datasets or commission tailored data and evaluation work, and enterprises also use its specialized agent solutions. Snorkel AI was founded in 2019 and is headquartered in San Francisco, California.

Company Size

201-500

Company Stage

Late Stage VC

Total Funding

$586.2M

Headquarters

Redwood City, California

Founded

2019

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Simplify's Take

What believers are saying

  • Expansion has new capital: September 2026 Snorkel raised $350 million in Series E financing.
  • Demand has scale: September 2026 Snorkel reported a $375 million annualized revenue run rate.
  • Employee wellbeing receives funding: Snorkel's benefits include a monthly wellbeing allowance and a company retirement match.

What critics are saying

  • Delivery margins need active management: Snorkel's delivery lead must challenge staffing decisions and control production costs.
  • Office attendance constrains delivery hires: Snorkel's Strategic Delivery Lead requires three office days weekly in San Francisco or New York.
  • Evaluation adds another quality layer: Snorkel's Senior SWE-bench separately judges AI-generated validation tests before accepting them.

What makes Snorkel AI unique

  • Research began with code-written labels: Snorkel's founding Stanford work combined imperfect labeling rules into training data.
  • Training data comes with a curriculum: Snorkel Data Series bundles difficulty tiers, grading rules, and evaluation slices.
  • Coding tests reflect senior work: Snorkel's Senior SWE-bench draws tasks from real pull requests across 12 repositories.

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Benefits

  • Health - Snorkelers and their dependents are covered by comprehensive medical, dental, and vision plans.
  • Environment - We provide an allowance for Snorkelers to set up workstations however they want.
  • Wellness - Snorkelers are given a yearly wellness stipend to be used on anything relating to health and well-being.

Growth & Insights and Company News

Headcount

6 month growth

2%

1 year growth

-5%

2 year growth

16%
SignalRaise
Sep 25th, 2026
Defense, data, and deep tech draw major capital this week.

Defense, data, and deep tech draw major capital this week. Five raises totaling over $1.5B this week show investors concentrating on AI infrastructure, autonomous defense systems, and science-driven platforms with verifiable traction. Defense AI commands a serious valuation. TEKEVER's $580 million Series D, reported by Tech.eu, values the Portuguese-founded autonomous drone and AI systems company at $6.4 billion [[1]]. The round followed the company's selection for the British Army's £400 million CORVUS programme - a government contract that gave investors a hard signal of real-world demand before they committed capital at that scale. The lesson for founders is structural: sovereign defense contracts function as a form of non-dilutive revenue validation. Investors in hardware-intensive, regulated categories increasingly want to see a government or enterprise anchor before writing a large check. If your company operates near defense, critical infrastructure, or aerospace, a contract win - even a pilot - may now be a prerequisite for a growth-stage raise rather than a bonus. Rapid ARR growth compressed the seed-to-A timeline. Chamelio returned to market just five months after closing its seed round, raising a $26 million Series A led by Entrée Capital, as Tech Startups reported [[2]]. The company attributed the accelerated timeline to ARR quadrupling over those five months. Bright Pixel Capital joined as a new investor alongside existing backers Work-Bench and Emerge Ventures. Five months between rounds is unusually short. What made it possible was not a product pivot or a new market narrative - it was a specific, auditable revenue metric moving in one direction. For founders at the pre-seed or seed stage, this round underscores that vertical AI agents with demonstrated enterprise adoption can compress normal fundraising timelines significantly. The implication: do not assume a standard 18-to-24-month runway before your next raise is necessary if your numbers justify going earlier. AI infrastructure attracted broad syndicate backing. Snorkel AI raised $350 million at a $3.5 billion valuation in a round co-led by Insight Partners and S32, with participation from Greylock, March Capital, Blumberg Capital, Allegis Capital, Frontline, Standard, Third Point Ventures, and Addition, as the company announced via PR Newswire [[3]]. The breadth of the syndicate - spanning early-stage specialists, crossover funds, and late-stage growth investors - is notable. Snorkel positions itself as a data infrastructure layer for frontier AI model development. Rounds of this composition signal that investors across stages see AI data pipelines as a foundational bet, not a niche one. For founders building in AI tooling or infrastructure, the size of this syndicate suggests that the conversation with growth-stage funds can start earlier than it once did - provided the infrastructure use case is clearly tied to model development or deployment at scale. Deep science rounds are getting larger and faster. Two science-driven rounds closed in quick succession. Precision Neuroscience raised $250 million in a Series D co-led by Bill Ackman's Pershing Square at a valuation just above $1 billion, bringing its total raised to $430 million, according to The Next Web citing a New York Times report [[4]]. Enveda, which uses AI to identify drug candidates in natural compounds, raised $311 million in a Series E at a $2 billion valuation led by Catalio Capital Management, as TechCrunch reported - a figure that doubles Enveda's valuation from twelve months prior [[5]]. Both rounds involve categories - brain-computer interfaces and AI-accelerated drug discovery - that carry long development timelines and high regulatory risk. What is drawing institutional capital in despite those risks appears to be the combination of AI-enabled speed (compressing discovery cycles) and the involvement of credible scientific and financial co-leads who can hold positions across multi-year horizons. For founders in biotech, neurotech, or other deep science verticals, the takeaway is that the investor pool has expanded: crossover funds and high-profile names outside traditional life sciences are now writing significant checks. This week, if you are raising. * If you are raising in defense, autonomous systems, or regulated hardware, pursue a government or enterprise anchor contract before approaching growth-stage investors - it is increasingly a prerequisite, not a differentiator. * If your ARR has multiplied in the past quarter, run the numbers on whether your traction already justifies returning to market ahead of schedule rather than waiting out a standard runway. * If you are building AI tooling or deep science platforms, map your round's potential syndicate across stage types - this week's raises show that early-stage specialists and large crossover funds are now co-investing in the same infrastructure and science bets. Sources. defense tech ai infrastructure biotech series a

SignalRaise
Sep 24th, 2026
AI agents and infrastructure dominate a week of nine-figure rounds.

AI agents and infrastructure dominate a week of nine-figure rounds. Five deals totaling over $5B closed in a single week, revealing a market that rewards vertical AI agents with real revenue and infrastructure bets at almost any scale. The stack gets funded from bottom to top. Three of this week's largest rounds sit at different layers of the AI supply chain, and together they sketch a picture of where institutional capital is concentrating. Crusoe, an AI infrastructure provider, announced the initial close of an anticipated $3.9 billion Series F at a $30.9 billion valuation, with Nvidia joining as a backer, as Channel Insider reported [[3]]. Snorkel AI, which builds data pipelines for training frontier models, closed a $350 million round co-led by Insight Partners and S32 at a $3.5 billion valuation, with a broad syndicate including Greylock and Third Point Ventures, according to a company press release [[4]]. Then Factory, which builds AI coding agents that sit on top of that infrastructure and data, raised $200 million from a group that includes Blackstone and Salesforce CEO Marc Benioff as an angel, as The Terminal reported [[1]]. Read together, these deals are not coincidental. Compute, data, and application-layer tooling are all being capitalized aggressively and simultaneously. For a founder raising at pre-seed or seed in the AI space, the implication is structural: investors are building conviction across the entire stack, not just at the model layer. A startup that connects clearly to one of those layers - faster training data, cheaper inference, or automated developer workflows - is speaking a language that is actively being funded. Factory's valuation jump resets expectations for agent Startups. Factory's trajectory this year is the kind of data point that changes how investors calibrate their own models. According to The Terminal, the company was valued at $1.5 billion in April 2026 and has now reached $5 billion - a more than triple increase in five months - on its third large check in under a year, with total funding now past $400 million [[1]]. The speed of that re-rating is notable: it happened without an exit or a public market event, purely on the basis of investor competition for a position. For founders building in the AI agent space, this sets a new benchmark for what "strong traction" can unlock in terms of valuation step-ups between rounds. It also signals that category leadership - being the recognizable name in a specific agentic workflow - may matter more right now than margin profile. What remains unclear from the available reporting is Factory's revenue trajectory or customer count, so whether this valuation reflects fundamental performance or competitive investor pressure is an open question. Vertical AI agents are closing rounds fast. Chamelio, a legal AI startup, raised a $26 million Series A led by Entrée Capital just five months after its seed round, according to Tech Startups [[2]]. The company says its annual recurring revenue quadrupled over that same period. Work-Bench, Emerge Ventures, and Bright Pixel Capital also participated. The new capital is earmarked for expanding the product and growing the team, though specific deployment plans were not detailed in the reporting. Five months from seed to Series A is a compressed timeline, and the ARR growth figure is the clearest explanation for why investors moved that quickly. For founders in vertical AI - legal, finance, HR, compliance - Chamelio's round reinforces a pattern that has appeared across several sectors this year: when a narrow AI agent demonstrably reduces cost or time in a high-stakes professional workflow, revenue can scale fast enough to justify an accelerated round. The sector specificity is a feature, not a constraint, because it makes the value proposition measurable. European defense tech draws sovereign and institutional capital. Tekever, a Portuguese-British autonomous drone startup, closed the first tranche of a $580 million Series D at a $6.4 billion valuation, with UC Investments and Baillie Gifford leading, as Tech Startups reported [[5]]. The raise comes as European governments accelerate spending on homegrown military technology, drones, and AI-enabled defense systems. This round is somewhat separate from the agent and infrastructure story, but it points to a macro dynamic worth tracking: government procurement tailwinds can compress the sales cycle and de-risk revenue projections in ways that make institutional investors more comfortable writing large checks. For founders in autonomous systems, robotics, or any dual-use AI category with a clear government customer, European defense budgets are now functioning as a credible demand signal that investors can underwrite. This week, if you are raising. * If your startup sits at any layer of the AI stack - compute, data, or application - map that position explicitly in your pitch, because investors are building coordinated conviction across all three layers simultaneously. * Chamelio's five-month seed-to-Series A path shows that measurable ARR growth in a vertical AI workflow can compress your timeline to the next round; track and lead with that metric in every investor conversation. * Factory's valuation tripling between rounds on investor competition alone means category positioning matters acutely right now - if you are not actively working to be the named leader in your specific agentic niche, a competitor is. Sources. ai agents startup funding infrastructure defense tech

MR Web
Sep 24th, 2026
Daily research news online.

Daily research news online. The global MR industry's daily paper since 2000. Follow DRNO on... Funding values AI data lab Snorkel at $3.5 billion. September 24 2026 Redwood City, CA-based Snorkel AI, whose data platform and agentic, research-driven data factory help inform AI model development, has raised $350 million in Series C funding, at a $3.5bn valuation. The firm says it will recruit researchers and engineers, to meet booming demand for complex training data. Snorkel is led by CEO Alex Ratner, and has developed an agentic data factory and expert Data-as-a-Service platform delivering data, benchmarks, evaluations and custom environments for frontier and agentic AI model development. Clients are AI labs and global enterprises in sectors including healthcare, law and software engineering, as well as the US Federal Government. Snorkel, which says it expects to reach profitability this year, combines human experts and thousands of specialized AI models and agents to create and check datasets. Quoted by Reuters, Ratner said experts devise design scenarios, tasks and grading rubrics, while AI automates much of the labor-intensive quality assurance process. The firm has built a network of 'tens of thousands of specialists' in coding, law, medicine and other fields. The round was co-led by Insight Partners and S32, with participation from Addition, March Capital, Blumberg Capital, Allegis Capital, Frontline, Standard, Third Point Ventures, Greylock, Lightspeed, GV, Factory, Prosperity7, Walden Catalyst and Wells Fargo. Home page: www.snorkel.ai. All articles 2006-23 written and edited by Mel Crowther and/or Nick Thomas, 2024- by Nick Thomas, unless otherwise stated. Most viewed items in the last week... Each (*) indicates > 1,000 views. Select a region below...

SignalRaise
Sep 23rd, 2026
AI infrastructure draws five large rounds in one week.

AI infrastructure draws five large rounds in one week. From memory chips to data labeling, investors are writing checks well above $200M for every layer of the AI stack, reshaping what 'infrastructure' means for founders raising now. The week's numbers in context. Five rounds closed or announced in roughly five days: Crusoe at an anticipated $3.9 billion Series F [[2]], Snorkel AI at $350 million [[3]], Positron AI at $875 million [[4]], Cornelis at $205 million [[5]], and Factory at $200 million [[1]]. Taken together, that is more than $5.5 billion committed to companies working on compute, memory, networking, data, and AI-native software in a single week. The pace is not normal, and founders raising at any stage should understand what it signals before they step into investor conversations this quarter. The rounds span multiple layers of the stack deliberately. Investors are not crowding into one category - they are betting that the entire infrastructure beneath foundation models remains undersupplied. That logic has direct consequences for how VCs evaluate market-size claims and competitive positioning in pitches right now. What is pulling the largest checks. The two largest rounds went to companies attacking physical constraints in AI compute. Positron AI closed an $875 million Series C at a $5 billion valuation on the thesis that LPDDR memory architecture can outperform the high-bandwidth memory Nvidia ships with its GPUs, framing bandwidth to memory - not raw processing power - as the real bottleneck in inference workloads, as pbxscience.com reported [[4]]. Crusoe, which provides AI compute infrastructure, announced the initial close of a round expected to reach $3.9 billion at a $30.9 billion valuation, with Nvidia itself participating, according to Channel Insider [[2]]. Nvidia backing a company that sells capacity built around GPU clusters is a signal about where demand is heading, not just an endorsement of one startup. Cornelis raised $205 million to launch what it describes as Active Compute Fabric, an open networking architecture that embeds programmable compute directly into the interconnects linking AI systems at scale, as Pulse2 reported [[5]]. The argument is that networking is no longer passive plumbing; it is a place where computation can happen. That framing - turning a cost center into a differentiated layer - is exactly the kind of narrative that attracted this round. Data and software attract serious capital too. Snorkel AI closed $350 million at a $3.5 billion valuation in a round co-led by Insight Partners and S32, with participation from Addition, Greylock, March Capital, Blumberg Capital, Allegis Capital, Frontline, Standard, and Third Point Ventures, according to a company press release [[3]]. The breadth of that syndicate - established growth funds alongside earlier-stage names - suggests investors see data infrastructure as a durable category, not a transitional one that gets absorbed once foundation models improve. Factory's round is the outlier in this group because it sits closest to the application layer. The AI coding-agent company raised $200 million at a $5 billion valuation, up from $1.5 billion five months earlier, with backing from Blackstone and Salesforce CEO Marc Benioff as an angel, as theterminal.space reported [[1]]. That is a more than three-times increase in valuation in under half a year, and it is the company's third large check in under twelve months. The speed of re-marking suggests investors are competing for allocation, not deliberating over it. What this means if you are raising pre-seed through Series A. The visible rounds this week are all late-stage, but the dynamics they create reach earlier in the funnel. When large funds deploy hundreds of millions into infrastructure bets, they need portfolio companies at every layer to succeed for the thesis to pay off. That creates downstream demand for early-stage companies that sell to, integrate with, or reduce costs for the Crusoes and Snorkels of the market. A pre-seed or seed founder who can articulate a credible relationship to the infrastructure build-out - as a customer, a tooling layer, or a distribution channel - is speaking directly to what investors are tracking this quarter. The Factory re-rating also sets a benchmark that cuts both ways. Investors who missed that round, or who passed on similar companies at lower valuations, are sensitized to moving faster. But the same data point raises the bar on what 'fast growth' means in AI software. If a $1.5 billion company can become a $5 billion company in five months, investors will ask founders raising Series A rounds why their trajectory does not look similar. Be prepared to answer that question with specifics, not projections. This week, if you are raising. * Map your startup to a specific layer of the AI stack - compute, memory, networking, data, or software - and use this week's rounds to show investors you understand where capital is concentrating and why your position benefits from it. * If you are in AI software or tooling, prepare a concrete answer to valuation velocity questions: Factory's five-month, three-times re-rating will prompt investors to ask why your growth curve looks the way it does. * Study the Snorkel AI syndicate structure - co-leads from Insight and S32 alongside seven other named participants - as a template for how to think about building a round with both institutional anchors and strategic smaller checks rather than chasing a single lead investor. Sources. ai infrastructure startup funding series a venture capital

PR Newswire
Sep 22nd, 2026
Snorkel AI raises $350M to scale the Data factory for frontier AI.

Snorkel AI raises $350M to scale the Data factory for frontier AI. Sep 22, 2026, 18:15 ET SAN FRANCISCO, Sept. 22, 2026 /PRNewswire/ - Snorkel AI, the frontier AI data lab, today announced it raised $350 million at a valuation of $3.5B in a round co-led by Insight Partners and S32, with significant participation from existing investor Addition. The round included new investors March Capital, Blumberg Capital, Allegis Capital, Frontline, Standard, and Third Point Ventures, along with existing investors Greylock, Lightspeed, GV, Factory, Prosperity7, Walden Catalyst, and Wells Fargo. The investment will expand Snorkel's agentic data factory, which supplies the data and environments behind the world's most advanced AI lab systems. The raise comes amid a fundamental phase shift in AI data. Building AI in the Data 1.0 era meant simple labeling tasks, a volume problem solved with headcount. Today's frontier and agentic systems demand Data 2.0: expert agentic tasks, environments, and rubrics that take even the most qualified humans hours or days to construct. Designing them well is research work, where quality and complexity determine value. Meeting that bar requires a wholly new paradigm for data development, which is partly why Snorkel has grown rapidly since launching its expert Data-as-a-Service offering in September 2025. The company works with leading AI labs and enterprises on the data behind frontier model evaluation and training. The work is a natural outgrowth of Snorkel's roots: the company grew out of the Stanford AI Lab nearly a decade ago with a founding team that pioneered the field of data-centric AI and continues to contribute science on data at the jagged frontier of AI development. That body of work spans 250+ peer-reviewed papers cited more than 25,000 times. "The teams pushing the frontier want a research data partner who pioneers the science of data development," said Alex Ratner, co-founder and CEO of Snorkel AI. "That's what Snorkel was built to be: the frontier lab for agentic data, combining human excellence with over a decade of research and technology." "Snorkel's research-grade approach to AI data, environments, and measurement is becoming an increasingly important ingredient in building capable and reliable AI systems - and their demonstrated growth at scale reflects that," said Lonne Jaffe, Managing Director at Insight Partners. "We're excited to back Alex and the team as they continue to bring their frontier AI data factory capabilities to longer-running, complex work in high value industries like healthcare, law, and software engineering." "Snorkel's expert-agentic environments create a unique flywheel between human expertise and AI, delivering data at the speed and quality that enables a new era of efficiency and accuracy for model development," said Andy Harrison, CEO and General Partner of S32. "Working with Snorkel ensures the highest frontier model success rate and creates a true partnership between model developer and data provider." Snorkel plans to use the funding to grow the capacity of its agentic data factory to meet demand, accelerate investment in vertical and enterprise AI, and extend its core research and technology into new domains and modalities. The company will also deepen its investment in open research, building on programs like its Open Benchmarks Grants initiative. About Snorkel AI Snorkel AI is the frontier AI data lab, helping teams build the data and environments behind high-performing frontier and agentic AI. We combine technology with research-driven AI data development to create datasets, benchmarks, evals, and custom solutions for real-world AI systems. Founded out of the Stanford AI Lab in 2019, Snorkel works with leading AI labs and enterprises to move from better data to better outcomes. About Insight Partners Insight Partners is a global software investor partnering with high-growth technology, software, and Internet startup and ScaleUp companies that are driving transformative change in their industries. As of December 31, 2025, the firm has over $90B in regulatory assets under management. Insight Partners has invested in more than 900 companies worldwide and has seen over 55 portfolio companies achieve an IPO. Headquartered in New York City, Insight has a global presence with leadership in London, Tel Aviv, and the Bay Area. Insight's mission is to find, fund, and work successfully with visionary executives, providing them with tailored, hands-on software expertise along their growth journey, from their first investment to IPO. For more information on Insight and all its investments, visit insightpartners.com or follow us on X @insightpartners. SOURCE Snorkel AI