About the Role 

In this role, you will build and lead our forward-deployed engineering (FDE) team, working directly with leading labs and enterprises to scope, build and deliver high quality datasets to support their most critical AI initiatives. 

You’ll lead a team that will own quality in the end-to-end data pipeline. This will include working with customers to define what “good” data looks like to implement the relevant workflows in their platform. You will design innovative ML approaches to enhance human-in-the-loop (HITL) techniques and improve the efficiency of data generation and review processes. Your team will own systems and tools that enable consistent, scalable, and high-quality data delivery to our customers.

Sitting at the critical intersection of data engineering, ML engineering, operations, and customer engagement— leading scoping and preselling efforts.  You'll also partner closely with the Snorkel delivery team and cross-functional stakeholders to define quality standards, develop measurement frameworks, drive ML-based workflows to improve data pipelines and unblock projects through technical innovation. As the founding member, you’ll also roll up your sleeves to define and own the workflows and processes that are needed to deliver exceptional data at scale.

Main Responsibilities

• Build and lead the Forward Deployed Engineering DaaS organization, setting a clear vision, defining the operating model and scaling its impact across Snorkel’s Expert Data-as-a-Service workflows
• Build, mentor, and motivate high performing teams, including cultivating skills and culture needed to consistently deliver exceptional outcomes and transformative impact. 
• Own and evolve the data pipeline components of the DaaS stack, including model-assisted labeling and data generation, quality estimation, and data-centric feedback loops that guide human input
• Partner with customers - including research and engineering teams at Frontier AI Labs - to scope requirements for complex, novel AI datasets and translate needs into delivery-ready workflows 
• Develop robust systems for request intake, task orchestration, SLA tracking, and progress monitoring to ensure seamless execution and prevent critical delivery gaps
• Collaborate cross-functionally with research and engineering teams to innovate, develop, and productionize HITL data generation methods, advanced quality techniques, and improve internal delivery tooling
• Drive continuous improvement by developing reusable workflows, surfacing operational insights, and enabling the organization to scale faster while maintaining high quality

What We’re Looking For

• 10+ years of experience in applied data or ML engineering roles, including 5+ years leading high-performing technical teams in hands-on management capacity
• Demonstrated success in customer facing roles, with a strong enthusiasm for data pipelines and LLM-based workflows.
• Proven track record of managing technical field teams in fast-paced, delivery-focused environments with competing priorities
• Experience as a player-coach—comfortable being hands-on while supporting and scaling the team
• Proven ability to thrive in fast-paced, ambiguous environments with cross-functional stakeholders
• Strong practical experience with LLM-based workflows, Python, SQL, and data tooling (e.g., pandas, Plotly, Streamlit, Dash)
• Bonus: experience working with data annotation workflows or internal tooling for data delivery orgs

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 found a function and have a broad, lasting impact across the company.

About the Role

Snorkel AI is hiring engineers who will work directly on Snorkel projects,  partnering with leading labs and enterprises to design, develop, and deliver high quality AI/ML data products for their most critical AI initiatives. This is a high-impact role focused on end-to-end ownership of the AI data pipeline lifecycle. This includes developing and deploying ML-based workflows, and building the technical foundations that make our human-in-the-loop (HITL) data generation and review faster 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 evaluation workflows, implement quality standards, measurement frameworks, and ML-assisted applications which improve our data pipelines and unblock projects through technical innovation.

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.

Main Responsibilities

Project Execution & Delivery

• Build and deploy evaluators, design and implement quality measurement systems to validate project outputs and ensure deliverables meet client expectations
• Generate synthetic datasets by developing or adapting existing pipelines to accelerate client engagements and augment training data
• Package and deliver production-grade datasets with standardized formatting, comprehensive documentation, and quality assurance
• Configure and build custom applications and off-platform solutions for non-standard or specialized client requirements

Production & Technical Partnership

• Define production specifications and workflows, securing technical alignment with client teams to enable seamless go-live transitions
• Provide ongoing technical support to Delivery Managers, addressing complex questions, resolving technical blockers, and supporting customer rebuttals
• Maintain specification consistency and alignment across customer and internal teams throughout the engagement lifecycle
• Identify and document workflow best practices and automation opportunities, collaborating with DaaS Engineering to continuously improve delivery capabilities

Technical Leadership & Innovation

• Maintain solution leaderboards and execute custom model benchmarking on existing datasets to demonstrate technical capabilities
• Drive continuous improvement of technical assets, evaluation frameworks, and delivery processes to enhance speed, quality, and scalability

What We’re Looking For

• 4+ years of experience in data science, engineering, or solution development roles. Strong practical experience with Python and SQL data tooling required
• Familiarity with ML and LLM-based solutions, applying ML techniques in production contexts, and validation and evaluation of ML and LLM-based
• Experience integrating systems via API

Compensation range for Tier 1 locations of San Francisco Bay Area and New York City, $172K - $300K OTE. All offers also include equity in the form of employee stock options. Our compensation ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.

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 own technical data workflows and be a founding member of the technical DaaS team. 

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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.