Research Engineer, Evaluations

Job Description

Meta is seeking Research Engineers to join the Evaluations team within Meta Superintelligence Labs. Evaluations are the core of AI progress at MSL, determining what capabilities get built, which features get prioritized, and how fast our models improve. As a Research Engineer on this team, you will curate and build the benchmarks for our most advanced AI models, across text, vision, audio, and beyond. You'll work alongside world-class researchers and engineers to collect, develop, and deploy novel benchmarks and reinforcement learning environments. This is a highly technical role requiring solid research engineering skills and the ability to work independently on a variety of open-ended machine learning challenges with high reliability. The evaluations you build will directly impact the research direction and major model lines within MSL, making engineering reliability, rigor, and scalability paramount. You will excel by maintaining high velocity while adapting to rapidly shifting priorities as we advance the technical research frontier. You'll need to be flexible and adaptive, tackling a wide variety of problems in the evaluations space, from implementing existing benchmarks to developing novel benchmarks and environments to implementing evaluation tooling at scale. If you are passionate about defining the capabilities that drive AI progress and thrive in fast-paced, high-impact research environments, we encourage you to apply for this exciting opportunity at the core of MSL.

Research Engineer, Evaluations Responsibilities

• Curate and integrate publicly available and internal benchmarks to direct the capabilities of frontier model development
• Develop and implement evaluation environments, including environments for novel model capabilities and modalities
• Collaborate with external data vendors to source and prepare high-quality evaluation datasets
• Execute on the technical vision of research scientists designing new benchmarks and evaluations
• Build robust, reusable evaluation pipelines that scale across multiple model lines and product areas
• Contribute to evaluation tooling that measures the quality and reliability of evaluation suites

Minimum Qualifications

• Currently has, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta
• Bachelor's or Master's degree in Computer Science, Machine Learning, or a related technical field
• 1+ years of experience in machine learning engineering, machine learning research, or a related technical role
• Proficiency in Python and experience with ML frameworks such as PyTorch
• Experience identifying, designing and completing medium to large technical features independently, without guidance
• Demonstrated experience in software engineering practices including version control, testing, and code review practices
• Ability to work independently and adapt to rapidly changing priorities

Preferred Qualifications

• Publications at peer-reviewed venues (NeurIPS, ICML, ICLR, ACL, EMNLP, or similar) related to language model evaluation, benchmarking, or deep learning
• Hands-on experience with language model post-training and deep learning systems, or building reinforcement learning environments
• Experience implementing or developing evaluation benchmarks for large language models and multimodal models (e.g., vision-language, audio, video)
• Experience working with large-scale distributed systems and data pipelines
• Familiarity with language model evaluation frameworks and metrics
• Track record of open-source contributions to ML evaluation tools or benchmarks

About Meta

Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.

Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.

Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@meta.com.

Key skills/competency

• AI Model Evaluation
• Machine Learning Engineering
• Python Programming
• PyTorch Framework
• Benchmark Development
• Deep Learning Systems
• Distributed Systems
• Data Pipelines
• Software Engineering Practices
• Research & Development