Job description

About Snorkel Snorkel AI is the frontier AI data lab, helping teams build the data and environments behind high-performing frontier and agentic AI. We combine technology with research-driven AI data development to create datasets, benchmarks, evals, and custom solutions for real-world AI systems. Founded out of the Stanford AI Lab in 2019, Snorkel works with leading AI labs and enterprises to move from better data to better outcomes. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler! About the Role Snorkel AI is hiring a Manager, Forward Deployed Engineering to build and lead our Forward Deployed Engineering (FDE) function within the Data-as-a-Service (DaaS) organization. This team is responsible for the technical execution layer of DaaS delivery — owning the systems, workflows, and quality frameworks that power high-quality dataset production at scale. You will lead a team of engineers who operate across the full AI data lifecycle: designing evaluation systems, building ML-assisted workflows, and developing the technical foundations that make human-in-the-loop (HITL) data generation faster, more reliable, and scalable. This is a hands-on, player coach role where you’ll both help define the strategy and architecture of our data pipelines while staying close to implementation. As a founding leader, you will establish how FDE partners with Delivery, Engineering, and Research to ensure consistent, high-quality execution across all DaaS projects. You’ll operate at the intersection of data engineering, ML engineering, and production operations, driving the evolution of our technical delivery capabilities and enabling Snorkel to scale its impact across increasingly complex AI workloads. Main Responsibilities Build and lead the Forward Deployed Engineering function, defining the team’s operating model, technical roadmap, and standards for execution Hire, mentor, and develop a high-performing team, fostering strong ownership, velocity, and engineering excellence Own the design and evolution of end-to-end AI data pipelines, including dataset generation, evaluation systems, and quality frameworks Drive development of ML-assisted and HITL workflows that improve the speed, scalability, and reliability of data production Establish and standardize measurement, benchmarking, and validation systems to ensure consistent, high-quality dataset delivery Develop scalable internal tooling and workflows for orchestration, monitoring, and delivery, reducing bottlenecks and improving throughput Partner cross-functionally with Delivery, Engineering, and Research to productionize new approaches and continuously improve DaaS capabilities What We’re Looking For 6+ years of experience in AI/ML/GenAI engineering, forward deployed engineering, solution engineering or applied AI roles, with strong hands-on technical depth 2+ years of experience leading or managing engineers in a hands-on, player-coach capacity Strong experience building and operating data pipelines and ML/LLM-based workflows in production environments Proficiency in Python, SQL, and modern data tooling; experience integrating systems via APIs. Has written code in the last 2 years Experience designing evaluation frameworks, quality measurement systems, or benchmarking approaches for ML systems Strong systems thinking — ability to design scalable, reusable solutions rather than one-off implementations Proven ability to operate in ambiguous, fast-paced environments and drive execution across cross-functional teams. Start-up or growth-stage experience is strongly preferred. Customer-facing, consulting, or services experience is strongly preferred Nice to have: Experience with human-in-the-loop (HITL) systems, data annotation workflows, or data-centric AI approaches. Familiarity with synthetic data generation or model-assisted labeling techniques. Experience building internal platforms or tooling for delivery or operations teams Why Join Snorkel AI? At Snorkel AI, we're building the future of data-centric AI. Our Expert Data-as-a-Service organization partners with world-class customers to solve some of the hardest data challenges — creating training and evaluation data that power the next generation of LLMs and AI systems. You'll work directly on projects that impact real production systems, while shaping how internal teams deliver faster, better, and more intelligently. This is a rare opportunity to find a function and have a broad, lasting impact across the company. Compensation The base salary range for this position is $200,000 – $320,000 . This range reflects multiple factors, including role level and work location. The final offer within this range will be determined based on job-related skills, experience, relevant education or training, interview performance, and other business considerations. Most offers include equity and benefits. Actual compensation will be determined based on factors including skills, qualifications, experience, and geographic location. Salary range(s) for this role $200,000 — $320,000 USD Be Your Best at Snorkel Joining Snorkel AI means becoming part of a company that has market proven solutions, robust funding, and is scaling rapidly—offering a unique combination of stability and the excitement of high growth. As a member of our team, you’ll have meaningful opportunities to shape priorities and initiatives, influence key strategic decisions, and directly impact our ongoing success. Whether you’re looking to deepen your technical expertise, explore leadership opportunities, or learn new skills across multiple functions, you’re fully supported in building your career in an environment designed for growth, learning, and shared success. Snorkel AI is proud to be an Equal Employment Opportunity employer and is committed to building a team that represents a variety of backgrounds, perspectives, and skills. Snorkel AI embraces diversity and provides equal employment opportunities to all employees and applicants for employment. Snorkel AI prohibits discrimination and harassment of any type on the basis of race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local law. All employment is decided on the basis of qualifications, performance, merit, and business need. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

Requirements

Must-haves

Build and lead the Forward Deployed Engineering function, defining the team’s operating model, technical roadmap, and standards for execution
Hire, mentor, and develop a high-performing team, fostering strong ownership, velocity, and engineering excellence
Own the design and evolution of end-to-end AI data pipelines, including dataset generation, evaluation systems, and quality frameworks
Drive development of ML-assisted and HITL workflows that improve the speed, scalability, and reliability of data production
Partner cross-functionally with Delivery, Engineering, and Research to productionize new approaches and continuously improve DaaS capabilities
What We’re Looking For
6+ years of experience in AI/ML/GenAI engineering, forward deployed engineering, solution engineering or applied AI roles, with strong hands-on technical depth
2+ years of experience leading or managing engineers in a hands-on, player-coach capacity
Strong experience building and operating data pipelines and ML/LLM-based workflows in production environments
Proficiency in Python, SQL, and modern data tooling; experience integrating systems via APIs. Has written code in the last 2 years
Experience designing evaluation frameworks, quality measurement systems, or benchmarking approaches for ML systems
Strong systems thinking — ability to design scalable, reusable solutions rather than one-off implementations

Nice-to-haves

Proven ability to operate in ambiguous, fast-paced environments and drive execution across cross-functional teams. Start-up or growth-stage experience is strongly preferred.
Customer-facing, consulting, or services experience is strongly preferred
Experience with human-in-the-loop (HITL) systems, data annotation workflows, or data-centric AI approaches.
Familiarity with synthetic data generation or model-assisted labeling techniques.
Experience building internal platforms or tooling for delivery or operations teams
Why Join Snorkel AI?

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimlllmpythonsql

Platform: greenhouse
Effort: quick