Senior Data & ML Pipeline Engineer, DaaS

FDE Times; New York (NY); Presencial; USD 180 000 - 320 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Equity

Benefits

Resumo da oferta

Snorkel AI is seeking an engineering delivery professional to own the AI data pipeline lifecycle, from data generation to ML-assisted workflows. You’ll translate client needs into production-grade solutions, work across data science, data engineering, and AI operations, and partner with the DaaS Delivery Operations team.

The role emphasizes cross‑functional collaboration, technical leadership, and the delivery of scalable data products for real-world AI systems.

Qualificações

• 5+ years of experience in data science, data engineering, ML engineering, or related roles.
• Strong practical experience with Python and SQL data tooling.
• Familiarity with ML and LLM-based solutions, including production workflows.
• Experience translating ambiguous requirements into technical specifications and workflows.
• Experience integrating systems via APIs and building custom tooling.

Responsabilidades

• Build and deploy evaluators and quality measurement systems to validate outputs.
• Generate synthetic datasets by developing or adapting pipelines for client engagements.
• Package and deliver production-grade datasets with documentation and QA.
• Define and build production specifications and workflows for seamless go-live transitions.
• Provide ongoing technical support to Delivery Managers and resolve blockers.
• Maintain specification consistency across customer and internal teams.
• Identify workflow best practices and automation opportunities with DaaS Engineering.
• Maintain solution leaderboards and benchmark models to demonstrate capabilities.

Conhecimentos

Python

SQL

Descrição da oferta de emprego

Snorkel AI is seeking an engineering delivery professional to own the AI data pipeline lifecycle, from data generation to ML-assisted workflows. You’ll translate client needs into production-grade solutions, work across data science, data engineering, and AI operations, and partner with the DaaS Delivery Operations team.

The role emphasizes cross‑functional collaboration, technical leadership, and the delivery of scalable data products for real-world AI systems.