Frontier AI Researcher & Data Environments Lead

Snorkel AI; New York (NY); On-site; USD 180,000 - 300,000; Full time

Benefits offered by this job

Health and dental coverage

Equity grants

Job summary

Snorkel AI is seeking Forward Deployed Researchers to partner with frontier AI labs on complex data problems. This high-impact, customer-facing role blends technical research with client engagement to design data environments that improve frontier model performance.

Responsibilities include scoping data needs, developing RL environments, evaluation frameworks, and translating customer objectives into actionable technical plans.

Qualifications

• Strong expertise in frontier AI concepts incl. LLMs and data pipelines.
• Experience in applied ML research or data science roles.
• Customer-facing or collaborative research experience preferred.
• Proficiency with Python and ML frameworks; familiarity with LLM APIs.

Responsibilities

• Own a technical domain end to end and define the next build.
• Design datasets/environments with frontier AI labs to boost model performance.
• Lead technical conversations with customer researchers on capabilities and data needs.
• Systematically evaluate model behavior to identify weaknesses and data interventions.
• Benchmark models against datasets and derive pass-rate analyses and recommendations.
• Develop evaluation frameworks and quality rubrics for project success.
• Create specifications for data projects balancing rigor and feasibility.
• Identify demand and opportunities across labs and customers.

Skills

LLMs

data pipelines

evaluation methodologies

post-training techniques

client engagement

Python

LLM APIs

communication

ambidexterity

Education

BS in Computer Science / ML / related field

4+ years AI/ML research or technical roles

Tools

Python

Containerized environments

ML frameworks

Job description

Snorkel AI is seeking Forward Deployed Researchers to partner with frontier AI labs on complex data problems. This high-impact, customer-facing role blends technical research with client engagement to design data environments that improve frontier model performance.

Responsibilities include scoping data needs, developing RL environments, evaluation frameworks, and translating customer objectives into actionable technical plans.