Project Lead, AI Model Training
New
J
JobgetherAI Data Operations
Remote work flexibility for candidates based in the U.S. or CanadaFull-TimeLead
Salary$150,000–$240,000
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Job Details
- Experience
- 3+ years
- Required Skills
- Project ManagementPythonSQLStakeholder managementProcess improvement
Requirements
- 3+ years of professional experience in data labeling, RLHF, SFT, AI evaluation delivery, or closely related AI data operations.
- Hands-on experience delivering real annotation or evaluation projects.
- Strong operational mindset with the ability to investigate quality metrics, diagnose workflow or queue issues, and resolve production problems.
- Demonstrated client-facing experience leading technical scoping discussions and managing expectations.
- Strong analytical capabilities and comfort working with data.
- Ability to manage several concurrent projects with different clients, quality requirements, and workflows.
- Strong attention to detail and a rigorous approach to quality, performance measurement, and delivery.
- Proven ability to operate effectively in ambiguous, rapidly changing environments.
- Builder mentality with a willingness to create processes, tools, documentation, and operating standards.
- Excellent communication, organization, prioritization, and stakeholder-management skills.
Responsibilities
- Lead AI training, evaluation, and data operations engagements end to end, from initial client scoping and project design through production, acceptance, delivery, and post-project review.
- Translate client objectives into clearly defined statements of work, task specifications, quality standards, annotator profiles, workflows, and evaluation criteria.
- Configure projects across the data operations platform, including task forms, grading rubrics, routing, multi-layer quality processes, and annotator enablement.
- Partner with ML leadership to develop initial guidelines and gold-standard datasets, rigorously testing project specifications before production begins.
- Own project quality, throughput, cost, and delivery timelines, monitoring performance against agreed targets and taking corrective action when metrics drift.
- Coordinate annotator pools by managing assignments, qualifications, access, performance, calibration, and escalations.
- Serve as the primary client contact throughout engagements, leading scoping discussions, progress updates, and acceptance testing.
- Build a scalable delivery organization by developing repeatable playbooks, templates, processes, and quality frameworks.
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