Meta
AI Specialist (Technical Leadership) - Product and Applied Research
$219K–$301K
Menlo Park, CA · Full-time · Posted Jul 24, 2026
- Experience
- 4+ years as a technical lead for a project of 4 or more individuals; also requires experience driving 0-1 AI product development.
- Education
- Bachelor’s degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience; a PhD or equivalent R&D experience is also listed.
About the job
Leads technical development of AI systems and products, shaping architectures and research methods while mentoring engineers and collaborating across teams to apply research to Meta products.
What you'll do
- Develop AI architectures, use cases, methodologies, and benchmarks; make system-level technical trade-offs.
- Lead and mentor cross-disciplinary teams, set technical direction, and drive AI product development.
- Collaborate with research and product partners, communicate complex systems, and develop and debug code.
What they ask for
- Bachelor’s degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience.
- Specialized experience in one or more of LLM post-training, agentic technology and product development, or Gen AI product applications; experience developing modeling algorithms or infrastructure in C/C++ or Python.
- Experience in one or more machine learning domains: NLP, recommendation systems, data mining, or information retrieval.
- 4+ years of experience as a technical lead for a project of 4 or more individuals; experience driving 0-1 AI product development.
Nice to have
- A PhD or equivalent R&D experience in Computer Science, Computer Engineering, or a relevant technical field.
- In-depth experience with LLM post-training alignment and reinforcement learning.
Pay
$219,000/year to $301,000/year USD base salary + bonus + equity
Tools
C/C++, Python, LLM
AI focus
Develops AI systems and products, including work in LLM post-training, agentic technology, generative AI applications, and machine learning; applies research to Meta products.
Model-written summary · the original posting is authoritative