Manager, Coder Fellows
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Role details
Tech stack
Job description
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., 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., * 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.
Requirements
- 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.
Benefits & conditions
This role is full time and will receive a base salary based on location and level plus equity., Actual compensation will be determined based on factors including skills, qualifications, experience, and geographic location. Salary range(s) for this role $175,000-$250,000 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.
About the company
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!
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