Forward Deployed Engineer - Data as a Service

Benefits

Parental leave

Not verified

Non-birth-parent leave

Not verified

Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

Not verified

Relocation assistance

Not verified

Childcare support

Not verified

Learning budget

Not verified

Verification

Not verified

Salary

$150K-$350K From the posting source checked Jun 20, 2026

401(k) match

Not verified

Was this benefit information wrong? Tell us.

Market context

U.S. role benchmark (BLS OEWS)

$116,543 U.S. median for this role

Projected growth (BLS Employment Projections)

+9.8% - Much faster than average

115% above the BLS role benchmark for software engineering aggregate.

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Engineering From the posting source checked Jun 20, 2026

Seniority

Mid From the posting source checked Jun 20, 2026

Work mode

Hybrid From the posting source checked Jun 20, 2026

In-office days

2 days From the posting source checked Jun 20, 2026

Schedule

Shift type

Not verified

Weekend work

Not verified

Company

Company stage

Growth-stage From the posting source checked Jun 20, 2026

Equity

Offered From the posting source checked Jun 20, 2026

Application

Cover letter

Not verified

Assessment

Not verified

Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

Forward Deployed Engineer - Data as a Service New York City, NY (Hybrid); Redwood City, CA (Hybrid); San Francisco, CA (Hybrid) About Snorkel At Snorkel, we believe meaningful AI doesn't start with the model, it starts with the data. We're on a mission to help enterprises transform expert knowledge into specialized AI at scale. The AI landscape has gone through incredible changes since 2015, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world's largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler! About the Role - Multiple Levels This is an engineering delivery role where you'll translate ambiguous customer needs into production-grade data, evaluation, and ML-assisted workflows. This is a high-impact role focused on end-to-end ownership of the AI data pipeline lifecycle, including developing and deploying ML-based workflows and building the technical foundations that make our human-in-the-loop (HITL) data generation and review faster, more reliable, and more effective. You'll work at the critical intersection of data science, data engineering, AI engineering and operations, partnering closely with our DaaS Delivery Operations team and cross-functional stakeholders. You'll develop technical specifications, design

Read the full description at job-boards.greenhouse.io. FewerJobs shows a preview and links to the original posting.