Expert Team Lead, Engineering

SpaceXAI•Palo Alto, CA

4d•$104,000 - $170,400•Hybrid

About The Position

SpaceXAI’s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company’s mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All employees are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates. 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.

Requirements

Bachelor's degree or higher in Mechanical, Electrical, Chemical, Civil, Environmental, or a closely related engineering field.
2+ Professional experience in engineering practice, such as design, analysis, testing, R&D, or systems integration OR a Master’s degree (or higher) in an engineering or engineering related field.
Basic understanding of AI and machine learning concepts and how high-quality training data impacts model performance.

Nice To Haves

Advanced degree (MS or PhD) in an engineering discipline, or professional licensure (PE, or FE/EIT).
Demonstrated experience with data quality metrics, annotation processes, and guideline-driven workflows (as evidenced by prior roles or projects).
Breadth across multiple engineering disciplines, with the ability to credibly review work outside your primary specialty.
Experience with performance management, coaching, training program development, and certification frameworks.
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.
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.

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.