Forward Deployed Engineer (Data as a Service)

Join Snorkel, a leading AI data platform, as a Forward Deployed Engineer. In this high-impact role, you will translate ambiguous customer needs into production-grade data and ML-assisted workflows. You will have end-to-end ownership of the AI data pipeline lifecycle, working at the intersection of data science, data engineering, AI engineering, and operations. You will develop technical specifications, design evaluation workflows, implement quality standards, and build ML-assisted applications. This role is ideal for someone with 3+ years of experience in data science, data engineering, or ML engineering, and strong practical experience with Python and SQL data tooling.

• Translate ambiguous customer needs into production-grade data, evaluation, and ML-assisted workflows.
• Develop and deploy ML-based workflows, build the technical foundations that make human-in-the-loop data generation and review faster, more reliable, and more effective.
• Work at the intersection of data science, data engineering, AI engineering, and operations, partnering closely with cross-functional stakeholders.
• This role is ideal for someone who is comfortable working throughout the delivery lifecycle, rolling up their sleeves to solve complex multi-faceted problems, thrives as a technical communicator and works well as a key member of a team
• 3+ years of experience in data science, data engineering, ML engineering, solutions engineering, forward-deployed engineering, or other technical solution development roles
• Experience integrating systems via APIs and building custom tooling or workflows for non-standard technical requirements
• Experience translating ambiguous customer or stakeholder requirements into technical specifications, workflows, and delivered solutions
• Strong practical experience with Python and SQL data tooling required
• Familiarity with ML and LLM-based solutions, including applying ML techniques in production contexts and building validation, evaluation, or quality measurement workflows for ML/LLM-based systems