Meta is looking for a Research Engineering Manager to lead the Evaluations team within Meta Superintelligence Labs. This role involves guiding a team of research engineers to build benchmarks for advanced AI models, ensuring high-quality evaluation infrastructure while collaborating with researchers and engineers.

• Bachelor's or Master's degree in Computer Science, Machine Learning, or a related technical field
• 4+ years of experience in machine learning engineering, machine learning research, or a related technical role
• 3+ years of experience managing or leading technical teams, including hiring, mentoring, and performance management
• Proficiency in Python and experience with ML frameworks such as PyTorch
• Proven track record of leading medium to large-scale technical projects from conception to deployment
• Demonstrated experience balancing hands-on technical work with people management and strategic planning
• Clear communication and experience influencing cross-functional stakeholders

• Build, mentor, and grow a team of research engineers and scientists focused on evaluation infrastructure and benchmarking
• Conduct performance reviews, career development conversations, and provide technical mentorship to team members
• Foster a culture of engineering excellence, research rigor, and rapid iteration within the team
• Curate and integrate publicly available and internal benchmarks to direct the capabilities of frontier model development
• Oversee the development and implementation of evaluation environments, including environments for novel model capabilities and modalities
• Establish partnerships with external data vendors to source and prepare high-quality evaluation datasets
• Influence the technical roadmap for evaluation infrastructure in collaboration with MSL Infra team
• Translate the technical vision of research scientists into actionable engineering plans and execution strategies
• Partner with research scientists, product teams, and other engineering teams to align evaluation priorities with organizational goals
• Build robust, reusable evaluation pipelines that scale across multiple model lines and product areas
• Drive the development of evaluation tooling that measures the quality and reliability of evaluation suites
• Maintain technical credibility through hands-on contributions to critical evaluation projects (20-30% of time)
• Review code, provide technical guidance, and unblock complex technical challenges
• Set engineering standards and best practices for the team

• Employees at Meta are often offered comprehensive benefits, including medical/dental/vision coverage, mental-health resources, family planning support (fertility, adoption, surrogacy), and caregiving programs. Financial benefits typically include a competitive retirement plan, equity awards, life insurance, and access to financial coaching and legal support. Time-off benefits commonly feature generous PTO and holidays, unlimited sick time, various paid leaves, flexible “Global Travel Days,” and a 30-day paid break every five years.