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Snorkel AI

Senior / Staff AI Engineer

Snorkel AI · New York City, NY (Hybrid); San Francisco, CA (Hybrid)

Posted 8 days ago

or apply directly on Snorkel AI's site. We never take the application ourselves.

Is this posting real?

This role has been open
8 days
Snorkel AI's roles stay open a median of 45 days
Reposted
No
Salary listed
No
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

As a Senior/Staff AI Engineer at Snorkel, you will design and build infrastructure for large-scale AI workloads, focusing on agentic systems and synthetic data generation. Your role involves creating evaluation frameworks, orchestration systems, and LLM infrastructure, ensuring that AI experiments are reproducible and measurable. You will collaborate with various teams to enhance the developer experience and turn experimental workflows into reliable production capabilities.

Our read on this posting3.2out of 5
benefits
1/5
freshness
5/5
career value
5/5
role clarity
5/5
pay transparency
0/5

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 building production software systems
  • Experience operating non-deterministic AI or ML workloads in production
  • Experience building infrastructure for experimentation, evaluation, model development, synthetic data, agentic workflows, training, inference, or production ML systems
  • Strong proficiency in Python
  • Strong background in distributed systems and cloud platforms (AWS preferred)
  • Experience with workflow or distributed execution frameworks such as Prefect, Airflow, Dagster, Ray, Kubernetes, or similar systems

Nice to have

  • Experience building or operating LLM or agent infrastructure
  • Experience building evaluation or experimentation platforms for LLMs, agents, or other probabilistic systems
  • Experience with synthetic data generation, automated labeling, data refinement, or dataset quality systems
  • Experience building reinforcement learning environments, agent simulations, benchmarks, or other environment-based evaluation systems
  • Experience running large-scale distributed AI workloads across containers, Kubernetes, serverless compute, sandboxes, or heterogeneous compute environments

Worth weighing

  • No salary listed
  • Role focuses on building infrastructure rather than training models or maintaining traditional ML pipelines
  • Fast-paced environment may require adaptability to rapidly evolving technologies

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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