Project Lead, AI Model Training

Jobgether; United States; Hybrid; USD 150,000 - 240,000; Full time

Benefits offered by this job

Stock buying program

Health insurance

401(k) with company match

Remote/hybrid work options

Job summary

Jobgether is seeking an experienced Project Lead for AI Model Training to manage data operations and end-to-end AI training engagements in the United States. You will translate client objectives into practical project plans, define workflows, and set evaluation criteria.

You’ll own quality, throughput, cost, and timelines while coordinating annotator pools and maintaining client communications. The role offers exposure to AI labs, senior leadership, and opportunities to scale a new AI-focused

Qualifications

• 3+ years of professional experience in data labeling, RLHF or AI evaluation delivery.
• Experience in data-labeling organizations, AI labs, or model-training operations preferred.
• Strong ability to analyze data, diagnose workflows, and improve rubrics and specs.
• Proven client-facing experience and ability to translate technical details into business outcomes.
• Comfort with SQL or Python is a significant advantage.

Responsibilities

• Lead AI training, evaluation, and data operations engagements end to end.
• Translate objectives into statements of work, workflows, and evaluation criteria.
• Configure projects with forms, rubrics, routing, and quality processes.
• Develop guidelines and gold-standard datasets before production.
• Own project quality, throughput, cost, and delivery timelines.
• Coordinate annotator pools, assignments, and performance.
• Serve as primary client contact during engagements and deliveries.
• Identify expansion opportunities and support new business discussions.
• Deliver repeatable playbooks, templates, and quality frameworks.

Skills

Data labeling

RLHF

SFT

AI evaluation delivery

Client-facing

SQL

Python

Tools

SQL

Python

Job description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Project Lead, AI Model Training based in United States.

This is a high-impact opportunity to lead complex AI training and evaluation engagements from initial scope through final delivery.

You’ll translate client objectives into practical project plans, quality standards, annotation workflows, and evaluation frameworks.

Working at the intersection of AI operations, data quality, and client delivery, you’ll manage multiple concurrent projects with demanding requirements.

You’ll own operational performance across quality, throughput, cost, timelines, and client satisfaction while solving issues before they become delivery risks.

The role offers significant exposure to AI labs, technical stakeholders, and senior leadership, with the opportunity to influence how next-generation AI systems are trained and evaluated.

As part of a growing delivery function, you’ll also create the playbooks, processes, and quality standards that enable the organization to scale.

This is an ideal role for an experienced AI data operations professional who enjoys hands‑on execution, client ownership, and building new systems in a fast‑moving environment.

Accountabilities

• 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 in partnership with the broader annotator delivery team.
• Maintain alignment across annotators through project channels, calibration sessions, updated guidance, and ongoing operational support.
• Serve as the primary client contact throughout engagements, leading scoping discussions, progress updates, quality conversations, escalations, acceptance testing, and final delivery.
• Manage client expectations transparently, identify acceptance issues early, and communicate operational challenges and solutions with confidence.
• Identify account expansion opportunities and emerging use cases, partnering with commercial teams and providing technical and operational expertise during new business discussions.
• Assemble and deliver project batches on schedule, manage client acceptance against agreed criteria, obtain sign‑off, and complete required project closeout activities.
• Conduct post‑project reviews and turn lessons learned into improvements to guidelines, tooling, workflows, quality standards, and future project scopes.
• Help build a scalable delivery organization by developing repeatable playbooks, templates, processes, and quality frameworks.
• Act as a key voice for delivery with product and engineering teams, identifying platform improvements based on real‑world project requirements.

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 is essential.
• Experience working at a data‑labeling organization, AI lab, model‑training operation, or comparable environment is strongly preferred; general project management experience alone is not sufficient.
• Strong operational mindset with the ability to investigate quality metrics, diagnose workflow or queue issues, resolve production problems, and improve evaluation rubrics or project specifications.
• Demonstrated client‑facing experience, with the ability to lead technical scoping discussions, manage expectations, communicate difficult information constructively, and translate operational details into business outcomes.
• Strong analytical capabilities and comfort working with data; experience using SQL or Python is a significant advantage.
• Ability to manage several concurrent projects with different clients, quality requirements, timelines, workflows, and annotator populations.
• Strong attention to detail and a rigorous approach to quality, performance measurement, and delivery.
• Proven ability to operate effectively in ambiguous, rapidly changing environments where processes may still be evolving.
• Builder mentality, with a willingness to create processes, tools, documentation, and operating standards rather than relying solely on established playbooks.
• Adaptable, resilient, and comfortable responding to changing client requirements, evolving specifications, and unexpected operational challenges.
• Excellent communication, organization, prioritization, and stakeholder‑management skills.
• High level of discretion and professionalism when handling client‑confidential information and annotator personal data under strict security and confidentiality requirements.
• Valid U.S. or Canadian work authorization required; visa sponsorship is not available for this role.

Benefits

• Competitive total on‑target compensation of $150,000–$240,000.
• Participation in a company stock buying program.
• Opportunity to help build and scale a new AI‑focused business unit from the ground up.
• Direct exposure to senior and C‑level leadership with significant opportunity to influence business and operational strategy.
• Fast‑track career growth opportunities toward operational and commercial leadership.
• Medical, dental, and vision insurance.
• 401(k) plan with immediate vesting and employer matching.
• Health Savings Account and Flexible Spending Account options.
• Pre‑tax commuter benefits.
• Paid vacation, holidays, sick leave, and parental leave.
• Collaborative, diverse, and supportive work culture.
• Team‑building activities, social events, projects, and company retreats.
• Remote work flexibility for candidates based in the U.S. or Canada, with hybrid work available in New York City.

How Jobgether Works

We use an AI‑powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top‑fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre‑contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.