Partner Engineering GenAI - US

About the role

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• Partner Engineering GenAI - US
• Partner Engineering GenAI - US
• Menlo Park, CA
• Partner Engineering
• + 1 more

We are seeking a Partner Engineer to join Meta’s GenAI Product Partners team, focused on enabling strategic partners to succeed with our generative AI products and platforms.

As a GenAI Product Partner Engineer, you bring in-depth experience in generative AI and associated tool stack, and will work closely with external partners to understand their technical requirements, design and ship solutions, and ensure seamless integration with our products.

You will be responsible for driving technical engagements, inventing new generative AI assets, building relationships with partners, and identifying opportunities to grow partnerships.

Partner Engineering GenAI - US Responsibilities

• Drive technical engagements with strategic GenAI partners to understand requirements and deliver solutions to complex problems
• Design, build, and integrate end-to-end generative AI systems and launch-plan strategies to meet partner needs
• Use broad range of technical and soft skills to build productive relationships with partners, and independently resolve complex technical and business needs
• Use expertise and product insight to deliver high-quality project/integration/partner engagements
• Work closely with product teams, guide workflow changes, and gain consensus from stakeholders while influencing product roadmap to meet the business needs
• Build and manage working relationships with partner technical counterparts and internal cross-functional teams
• Ship production level code, code reviews, and provide constructive feedback while quickly actioning feedback from code reviews conducted of your code
• Create technical content, tools, and documentation to empower developers and partners
• Contribute to the Meta AI developer ecosystem, including case studies, online courses, and best practices
• Influence decision-making through presentation and dissemination of data-centric analyses
• Bring in-depth experience in generative AI and associated tool stack, and provide consultation on domain-level projects
• Mentor peers, share knowledge, and promote collaboration, respect, and a positive team environment
• Participate in interviewing and onboarding of new team members

Minimum Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
• Bachelor's degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience
• 5+ years of experience in one or more of the following areas: Software Engineering, Artificial Intelligence, Machine Learning, or a related field
• 3+ years of experience in Deep Learning, Model Fine-tuning, Inference Optimization, or Distributed Systems
• Direct experience working with modern foundational AI architectures (e.g., Transformers, Mixture-of-Experts, or hybrid/multimodal architectures) beyond API interactions (e.g., hands-on experience with weights, tokenizers, kernels, and model internals)
• Solid understanding of at least one Deep Learning framework (e.g., PyTorch or JAX) and the ability to read, translate, and contribute to large-scale inference codebases
• Experience leading complex cross-functional (XFN) technical initiatives and communicating technical concepts to internal and external partners
• Development experience in languages like Python, Java, Go, Rust, C/C++. (at least one)
• Experience with generative AI tool stacks including LLMs such as LLaMA, GPT, Claude, etc
• Experience working with external partners, customers, or stakeholders to understand their technical requirements and deliver solutions
• Experience with cloud-based technologies, APIs, and data integration

Preferred Qualifications

• Experience executing end-to-end launch day operations for major AI releases, technical blogs, and developer repositories
• Active contributor to major open-source AI projects or experience managing public model release artifacts (e.g., SGLang, vLLM, llama.cpp, PyTorch)
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
• Direct experience enabling the use of agentic frameworks or AI coding tools
• Master’s or Ph.D. degree in Computer Science, Machine Learning, or a related technical field
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
• Deep, up-to-date knowledge of cutting-edge AI research papers and the ability to rapidly translate novel architectural concepts (e.g., test-time computation, speculative decoding, linear attention) into functional deployment code

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