Expert Team Lead, SWE
xAICodingFirst seen 9 Oct 2026
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- Where
- Worldwide
- Language
- English
- Type
- Contract, remote
- Field
- Coding
Posted on xAI First seen 9 Oct 2026Checked 12 Oct 2026
From the xAI listing
SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today, SpaceX is actively developing the technologies to make this possible, with the ultimate goal of making life multiplanetary and expanding consciousness to the stars.
SpaceXSI is building Super Intelligence to understand the universe and help expand humanity’s knowledge and capabilities. We work across the full Super Intelligence stack: compute (Colossus supercomputers), models (Grok), and applications (Grok Bot, Grok Build, Grok Imagine, Grok Voice, and X). We're creating a powerful flywheel where more compute trains better models, better models power more useful products, and what we learn from people using those products shapes what we build next.
ABOUT THE ROLE:
You will lead a team of AI Tutors (full-time employees and contractors) responsible for delivering high-quality training data and evaluations that power SpaceXAI's models. You will set the standard for data quality on your projects, review work in the domain, ensure the accuracy and consistency of the data produced, and build operational excellence at the team level. This is a hands-on leadership role, you will both execute labeling/review work and continuously improve processes as we scale.
RESPONSIBILITIES:
- Own end-to-end quality and delivery for assigned Human Data projects, personally reviewing work in the domain, ensuring accuracy, consistency, guideline adherence, and high-quality data production at scale.
- Lead, coach, and performance-manage a team of AI Tutors, including conducting regular performance reviews, maintaining records, creating action plans, managing shadow sessions, and driving continuous improvement.
- Oversee and actively participate in labeling and reviewing tasks to maintain high standards and model best practices.
- Ensure strict guideline adherence, taxonomy management, and quality assurance processes.
- Drive efficiency by identifying and resolving operational bottlenecks, implementing process improvements, and tracking performance via KPI dashboards (e.g., quality metrics, throughput, send-back rates).
- Build, update, and deliver training materials, practice tasks, and certification benchmark tasks; manage certifications and workforce adjustments.
- Collaborate closely with Human Data Managers, fellow Team Leads, and Engineering to translate model needs into clear labeling strategies and requirements.
- Coach and develop talent while maintaining strong accountability and a high-performance culture; support disciplinary actions as needed.
- Document outcomes, suggest process iterations, and report project status, risks, and results.
- Act as the voice of your tutors while fostering strong collaboration across the broader Human Data organization.
BASIC QUALIFICATIONS:
- 1+ years of hands-on experience in data labeling, annotation, AI training/evaluation, content quality, or similar operational domains.
- Professional experience building scalable, high-performance technology applications.
- Demonstrated experience with data quality metrics, annotation processes, and guideline-driven workflows (as evidenced by prior roles or projects).
- Basic understanding of AI and machine learning concepts and how high-quality training data impacts model performance.
- Experience with performance management, coaching, training program development, and certification frameworks.
PREFERRED SKILLS AND EXPERIENCE:
- Previous experience leading small teams in data labeling, annotation, or related operations.
- Proven ability to manage multiple concurrent projects and prioritize effectively in a fast-paced environment.
- Strong track record of reviewing domain work, ensuring data quality, and improving operational processes.
- Proficiency in data analysis and associated tools (SQL a plus); ability to use metrics and KPIs to drive continuous improvement.
- Experience managing mixed employment types (full-time employees and contractors) or distributed teams.
- Excellent verbal and written communication skills with the ability to build rapport quickly and align stakeholders.
- Strong organizational skills, high attention to detail, proactive problem-solving mindset, and focus on continuous improvement.
- Strategic thinking combined with strong hands-on execution.
- Specialty or strong domain expertise in at least one of the following areas: Finance, STEM, Coding/Software Engineering, or other technical fields.
- Passion for building high-performing teams and scaling high-quality Human Data operations.
ADDITIONAL REQUIREMENTS:
- Candidates must be based in one of the following countries where SpaceXAI has a physical office; remote work is also possible - United States - Dubai - Ireland - United Kingdom - Ireland - Japan - India - Indonesia - South Korea - Philippines - Singapore
COMPENSATION AND BENEFITS:
US based candidates: $104,000 - $170,400 USD depending on factors including relevant experience, skills, education, geographic location, and qualifications. International candidates: information will be provided to you during the recruitment process.
Base salary is just one part of our total rewards package at SpaceXAI, which also includes equity, comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short & long-term disability insurance, life insurance, and various other discounts and perks. Benefits vary based on employment type, location and jurisdiction. Benefits for eligible U.S. based positions include health insurance, 401(k) plan, and paid sick leave. Specific details and role specific information will be provided to you during the interview process.
SpaceXAI is an equal opportunity employer. For details on data processing, view our Recruitment Privacy Notice.
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Terms in this listing
- Labeling: Assigning a category or tag to an item, for example marking a review as positive or negative. Often used as a synonym for annotation.
- Taxonomy: The fixed list of categories a project uses for labeling, often with definitions and examples for each.
- Benchmark: A fixed set of test tasks used to compare models or track progress over time.
- Annotation: Adding labels or notes to data such as text, images, audio or video so a model can learn from it.
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