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Snorkel AI has 20 active AI-related job listings, with a strong emphasis on data-related roles, accounting for 75% of their openings. Engineering is the most frequent function, followed by Research. The majority of these positions are located in the United States. Their hiring activity shows a recent decrease, with 4 new AI roles posted in the last 30 days, a 50% reduction compared to the previous 30-day period.

Auto-generated from active job postings · last refreshed 2026-05-24

Currently tracking 18 active AI roles, down 13% versus the prior 4 weeks. Primary focus: Data · Engineering. Salary range $150k–$350k (avg $244k).

Hiring
18 / 21
Momentum (4w)
↓-2 -13%
13 opens last 4w · 15 prior 4w
Salary range · avg $244k
$150k–$350k
USD · disclosed roles only
Tracked since
Jan '25
last role 4w ago
Hiring velocityscroll left for older weeks
1 new role
Jan 20
1 new role
Jul 7
1 new role
Oct 6
1 new role
20
1 new role
27
1 new role
Nov 10
1 new role
17
1 new role
24
1 new role
Jan 5
1 new role
19
1 new role
Feb 9
2 new roles
23
2 new roles
Mar 2
8 new roles
9
4 new roles
16
2 new roles
23
5 new roles
30
2 new roles
Apr 6
5 new roles
13
5 new roles
20
4 new roles
27
4 new roles
May 4
3 new roles
11
4 new roles
18
5 new roles
25
3 new roles
Jun 1
2 new roles
8
3 new roles
15

Frequently asked questions

  • What AI roles is Snorkel AI hiring for?

    Snorkel AI currently has 18 active AI-related roles in our index. The most common open titles are: AI Advocate, Open-Source & Research, Applied AI Engineer - Federal (TS Required), Director, Research - Evaluation & Training, Director, Research - Frontier Benchmarks, Forward Deployed Engineer - Data as a Service. Most positions are in Engineering and Research.

  • What stage of AI development does Snorkel AI focus on?

    Snorkel AI's active AI hiring is concentrated in: data (72%), evaluation (11%), agents (11%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.

  • Where is Snorkel AI hiring AI talent?

    Snorkel AI is hiring AI talent in: United States (16 roles).

  • What technologies does Snorkel AI's AI team work with?

    Job postings at Snorkel AI most frequently reference: evals, synthetic data, fine tuning, agent orchestration, rl post training.

  • How many AI roles has Snorkel AI posted recently?

    In the past 30 days, Snorkel AI has posted 5 new AI-related roles.

Jobs (15)

15 AI · 44 total active
Show
Active onlyAI only (≥ 7)
Stage
AllData · 10Post-train · 1Agent · 2Eval Gate · 2
Function
AllEngineering · 7Research · 7Product · 1
Sort
AI scoreRecentTitle
TitleStageFunctionLocationFirst seenAI score
Research Scientist - Frontier Benchmarks
Research Scientist focused on developing frontier benchmarks and datasets for LLM training and evaluation, collaborating with academic partners and customers, and influencing company roadmap and research community.
DataEval GateResearchRedwood City, CA +1 · Remote4w ago9
AI Advocate, Open-Source & Research
AI Advocate role focused on open-source and research communities, acting as the primary technical voice for Snorkel AI. Responsibilities include creating technical content, leading open-source efforts, advancing AI evaluation and benchmarking, driving conference presence, and partnering with research teams. The role emphasizes translating Snorkel's data-centric AI methodology into practical applications and community engagement.
Post-trainAgentResearchSan Francisco, CA7w ago9
Staff/Principal Research Scientist
Research Scientist at Snorkel AI focused on designing, implementing, and validating novel AI techniques for data development, such as synthetic data generation using LLM as a Judge. The role involves prototyping and building end-to-end workflows, integrating research into scalable systems, and collaborating with partners to test solutions in applied settings. Emphasis on rapid iteration and driving innovation from research into production.
DataPost-trainResearchRedwood City, CA +1 · RemoteApr 139
Research Scientist
Research Scientist role focused on designing, implementing, and validating novel AI techniques for data development, such as synthetic data generation using LLM as a Judge. The role involves prototyping and building end-to-end workflows, integrating research ideas into scalable systems, and collaborating with partners to productionize prototypes. Emphasis on applied research and system-building in an enterprise AI context.
DataAgentResearchRedwood City, CA +1 · RemoteOct '259
Director, Research - Frontier Benchmarks
Director of Research at Snorkel AI, focusing on designing datasets to advance the frontier of AI. The role involves leading a team to identify data needs, design benchmarks, and collaborate with academic and industry partners. It sits at the intersection of research, product strategy, and go-to-market, with a strong emphasis on data-centric research and evaluation.
DataPost-trainResearchSan Francisco, CA1w ago8
Director, Research - Evaluation & Training
Snorkel AI is seeking a Director of Research to lead a team focused on data evaluation, error analysis, and data valuation methods to predict model performance. The role involves owning a roadmap for novel evaluation techniques, synthesizing trends from model failures, and quantifying the impact of Snorkel's data on model performance. This leadership position requires a strong understanding of the AI/ML landscape, team management experience, and the ability to translate technical findings into business outcomes.
Eval GateDataResearchSan Francisco, CA2w ago8
Senior Software Engineer - AI / ML
Senior AI/ML Engineer to join the AI Platform team, focusing on distributed systems, LLM infrastructure, synthetic data generation, and agentic orchestration. The role involves architecting the core platform, designing APIs and compute services, generating synthetic data, creating and evaluating agentic systems, provisioning RL training environments, deploying benchmarks and labeling pipelines, and running LLMs efficiently.
DataAgentEngineeringRedwood City, CA +1Apr 158
Head of Forward Deployed Engineering
Lead a forward-deployed engineering team focused on building and delivering high-quality datasets for AI initiatives. This involves defining data quality, implementing workflows, enhancing human-in-the-loop techniques, and owning systems for scalable data delivery. The role sits at the intersection of data engineering, ML engineering, and customer engagement, requiring strong leadership and hands-on technical skills in LLM-based workflows.
DataPost-trainEngineeringRedwood City, CA +1Mar 138
Senior Product Manager - Data & Quality
Senior Product Manager at Snorkel AI to lead development for agentic data systems, synthetic data systems, evaluations, and data-acceleration initiatives. The role involves defining product vision, roadmap, and execution plans for intelligent workflow systems, optimizing data pipelines, and improving task quality. Key responsibilities include owning the product vision for task and evaluation products, leading evaluation initiatives, defining performance metrics, building recommendation systems for task matching, and supporting enablement efforts.
Eval GateDataProductRedwood City, CA +1Mar 68
Senior Manager - Research
Snorkel AI is seeking a Senior Manager of Research to lead a team focused on data-centric research for next-generation foundation models. The role involves team building, frontier data research, strategic roadmapping for AI data bottlenecks, and operational excellence. The ideal candidate has 5+ years in applied AI/ML research, 4+ years managing technical teams, and practical experience with LLMs and agentic workflows.
DataPost-trainResearchSan Francisco, CAFeb 98
Applied AI Engineer - Federal (TS Required)
Applied AI Engineer at Snorkel AI, focusing on building and deploying Gen AI and ML solutions for customers, leveraging Snorkel Flow or custom approaches. Responsibilities include developing RAG, fine-tuning pipelines, prompt engineering, agentic workflows, creating datasets and evaluation workflows, and collaborating with customers and product teams. The role emphasizes bridging AI technology with business value and standardizing solutions into platform capabilities.
AgentDataEngineeringRemoteNov '258
Senior Software Engineer - Expert Data Collection Platform
Senior Full Stack Engineer to build and maintain an Expert Data Collection Platform that enables domain experts to provide high-signal data for training and refining AI models. The role involves end-to-end feature development, scalable service optimization, and user-focused interface design.
DataPost-trainEngineeringRedwood City, CA +1Mar 317
Manager, Forward Deployed Engineering
Manager for Forward Deployed Engineering (FDE) within the Data-as-a-Service (DaaS) organization. This role leads a team responsible for the technical execution of DaaS delivery, owning systems, workflows, and quality frameworks for high-quality dataset production at scale. Responsibilities include building and leading the FDE function, defining its operating model and roadmap, hiring and mentoring engineers, owning AI data pipelines (generation, evaluation, quality), driving ML-assisted and HITL workflows, establishing measurement and benchmarking systems, and developing internal tooling. The role requires strong hands-on technical depth in AI/ML/GenAI engineering, experience leading engineers, building/operating production ML/LLM workflows, proficiency in Python/SQL, and experience with evaluation frameworks.
DataEval GateEngineeringRedwood City, CA +1Mar 197
Staff Applied AI Engineer - Pre-Sales
Partner with Sales to lead technical discovery, solution scoping, and demo development for GenAI and ML solutions, translating customer needs into technical proposals and driving adoption of AI.
AgentDataEngineeringRedwood City, CA +1Mar 187
Forward Deployed Engineer - Data as a Service
Snorkel AI is seeking a Forward Deployed Engineer to work on AI/ML data products for enterprise clients. This role involves end-to-end ownership of the AI data pipeline lifecycle, including developing and deploying ML-based workflows, building HITL data generation and review processes, generating synthetic datasets, and packaging production-grade datasets. The engineer will also define production specifications, build evaluators, design quality measurement systems, and perform custom model benchmarking.
DataEval GateEngineeringRemoteOct '257