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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.
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.
About the Role
Coding Fellows create high-quality technical content used to train and evaluate AI systems. Depending on the project and each Fellow’s strengths, their work may include writing and reviewing code, opening pull requests, creating annotations or documentation, improving others’ work, and coaching peers.
We are looking for a leader to directly manage a portfolio of Fellows who may contribute across multiple projects over time. Project delivery teams own day-to-day tasks, priorities, and outcomes; this role owns the people-management layer across projects, including expectations, performance, support, development, administration, and a fair, consolidated view of each Fellow’s contribution.
This is a people-first role. You should have enough technical depth to understand and discuss Fellow work, but you will not be the day-to-day technical lead or approver for every project.
What You Will Do
Lead and Support Coding Fellows
Build trusted relationships through regular one-on-ones and ongoing communication. Understand each Fellow’s strengths, goals, challenges, and support needs; set clear expectations; and partner with People Operations and project leaders on onboarding and administrative matters.
Own Cross-Project Performance Management
Set expectations for quality, reliability, collaboration, communication, flexibility, learning, and professional conduct. Gather and synthesize feedback across projects, accounting for assignment complexity, project context, ramp time, and changing responsibilities. Recognize strong performance, provide candid feedback, and address concerns early through focused improvement plans.
Maintain Technical Credibility and Quality
Review representative work, including code, pull requests, reviews, annotations, documentation, and commentary, to understand quality and development needs. Partner with delivery and quality leads to identify recurring issues and distinguish individual performance concerns from unclear requirements, insufficient context, or process gaps.
Partner with Project Delivery Teams
Create effective feedback loops with project managers, technical leads, reviewers, and other delivery partners. Establish clear expectations when Fellows join projects, preserve context during transitions, surface assignment mismatches or blockers, and resolve conflicts with fairness and discretion.
Coach Growth and Strengthen the Program
Hold regular career conversations and help Fellows grow as individual contributors, reviewers, quality specialists, coaches, or mentors. Use contextualized metrics to monitor quality, throughput, reliability, team health, and retention; improve feedback and calibration processes; and contribute to hiring and workforce planning as the program scales.
What This Role Owns—and Does Not Own
You own: Fellow support, people administration, performance expectations, consolidated feedback, performance reviews, coaching, development, and long-term success.
Project delivery teams own: day-to-day task assignment, project-specific priorities, delivery plans, immediate deliverable acceptance, and project execution.
You will work closely with delivery teams, but you will not run every stand-up, manage every task, or assess performance using raw activity metrics alone.
What We Are Looking For
- 3+ years of experience in software engineering, technical leadership, or a related environment, including direct management of programmers or software engineers.
- A computer-science degree is not required. Experience with AI/ML development, model evaluation, annotation, data quality, or technical-content production is helpful.
- Demonstrated experience hiring, onboarding, coaching, conducting performance reviews, delivering actionable feedback, and handling difficult conversations.
- Experience managing people across multiple projects, clients, teams, or changing assignments.
- Experience in a consultancy, software agency, contract engineering shop, professional-services organization, staff-augmentation model, or similar distributed environment is strongly preferred.
- Enough technical depth to read and discuss code and pull requests, assess engineering judgment, and understand core software-development practices.
- Ability to evaluate performance thoughtfully rather than relying on throughput, ticket volume, or other simple metrics.
- Strong written and verbal communication, sound judgment, discretion, empathy, and a collaborative, low-ego approach.
What Success Looks Like
- Coding Fellows understand expectations, receive consistent support, and trust their manager.
- Performance reviews reflect evidence across projects—not a single assignment or raw activity metric.
- Delivery teams provide timely, specific feedback and know how to partner with the Coding Fellows Manager.
- Strong work is recognized, growth is visible, and performance concerns are addressed early.
- Fellows transition between projects with clear context and continuous support.
- The program improves quality, throughput, collaboration, communication, and retention without compromising fairness or the quality of the work.
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Snorkel AI
View Company ProfileSnorkel AI (operating at snorkel.ai) is a frontier AI data lab engineered for high-stakes domains. Founded in 2019 by Alexander Ratner and headquartered in Redwood City, California, Snorkel AI helps teams build the data and environments behind high-performing frontier and agentic AI. Under the hood, Snorkel AI specializes in image data labeling using a proprietary ML approach that utilizes programmatic labeling and statistical modeling to build specialized training data, benchmarks, and evaluation environments. This allows enterprises to develop AI that works for their unique workloads using their proprietary data and knowledge 10-100x faster. Backed by $238M in funding over 7 rounds.
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