Senior/Staff FDE - Synthetic Data Generation
Snorkel AI · New York City, NY (Hybrid); San Francisco, CA (Hybrid)
Posted 20 days ago · $180,000–$320,000
or apply directly on Snorkel AI's site. We never take the application ourselves.
Is this posting real?
- This role has been open
- 20 days Snorkel AI's roles stay open a median of 45 days
- Reposted
- No
- Salary listed
- Yes 42% of Snorkel AI's roles list one
- Ghost-job risk at Snorkel AI
- high 24 stale, 5 reposted of 38 open
- Hiring momentum
- 58 roles opened in the last 90 days ↑ up vs. the prior 90 days
- Last confirmed on the employer's board
- 2026-09-17
Measured from postings appearing on and disappearing from Snorkel AI's own greenhouse board since 2026-08-03. Full hiring picture for Snorkel AI.
About this role
The Senior/Staff Forward Deployed Engineer at Snorkel will focus on synthetic data generation to enhance AI model training and performance. Daily responsibilities include designing and building scalable data generation pipelines, translating model challenges into effective data strategies, and leading customer engagements from solution design to production delivery. The role also involves technical leadership, improving standards for synthetic data processes, and collaborating with customers and internal teams.
- benefits
- 2/5
- freshness
- 4/5
- career value
- 4/5
- role clarity
- 5/5
- pay transparency
- 5/5
Scored from the posting itself — how clearly the role is described, how much it says about pay and benefits, and how recently it was listed. Not a judgement of Snorkel AI as an employer.
What you need
- 5+ years of experience in machine learning engineering, data science, applied AI, forward deployed engineering, or a similar technical role
- Strong Python skills and experience building reliable production data or ML systems, including containerizing with Docker and deploying on cloud platforms (e.g., AWS, GCP, or Azure)
- Hands-on experience with LLMs—building model-based applications and data workflows with the modern GenAI/LLM stack, and integrating systems, models, and data sources through APIs
- Strong understanding of ML experimentation and evaluation, including defining metrics and using empirical results to guide technical decisions
- Experience building synthetic data, data augmentation, or model-generated training and evaluation datasets
- Experience with LLM evaluation techniques, including LLM-as-a-judge, model-based evaluation, rubric-based evaluation, or custom evaluators
Nice to have
- Experience developing datasets for fine-tuning, preference optimization, or benchmarking, including human-in-the-loop generation and review workflows
- Experience building agentic environments and tasks—repo-scale coding tasks, tool-agent-user interaction design, and agent tool protocols and interoperability
- Experience with reinforcement learning for LLMs, including reward and verifier design and RL with verifiable rewards (RLVR)
- Experience working in fast-paced, customer-facing environments where requirements and technical approaches evolve quickly
What you get
- Base salary range of $180,000–$320,000
- Additional variable compensation opportunity
- Equity in the form of employee stock options
- Opportunities for career growth and skill development
Worth weighing
- No specific mention of remote work flexibility beyond hybrid options in NYC and San Francisco
- Salary range provided, but actual compensation may vary based on multiple factors
- Role involves navigating ambiguity and complex technical challenges, which may require strong problem-solving skills
Summarised from Snorkel AI's posting. Read the full original.
Listed by Snorkel AI on their greenhouse job board, last confirmed open on 2026-09-17. PitchMeAI is not the employer.
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