Partner Engineer, Generative AI

Meta is seeking a Partner Engineer to join Meta’s AI Partner Engineering team, a technical team that works with strategic partners, machine learning organizations across the industry and all major cloud service providers for building and launching new Generative AI product services and experiences, and taking Large Language Models (LLMs) from research to production. In this role, you will engage with strategic partner companies and work closely with our Llama engineering and AI research teams.

You will also represent Meta at developer conferences and events. You will be required to develop technical accelerators, case studies, white papers, blogs, reference architectures, and/or presentations to evangelize Meta’s AI design patterns and best practices.

Partner Engineer, Generative AI Responsibilities:

Apply relevant AI and machine learning techniques to build and launch generative AI solutions using Meta’s Llama and other state of the art LLMsUnderstand Meta’s AI, Llama architecture, frameworks, products and their underlying implementation

Define and execute on a strategy to drive adoption of Llama and other Meta’s AI/ML platform offerings

Work closely with cloud providers (e.g. AWS, Azure, GCP) and Meta’s strategic partners on deep learning & Llama integrations

Serve as a technical point of contact for partners and internal teams at Meta, providing guidance on AI architecture and integration patterns

Evangelize Llama & Gen AI services and share best practices through forums such as medium blogs, whitepapers, reference architectures and public engagement events

Develop reference architectures, samples and other materials to share with the broader Meta developer community

Work with key partners and Llama developer community to optimize existing generative AI models for improved performance, scalability, and efficiency

Lead technical strategy and roadmap for long-term strategic partners with high level of autonomy to own and navigate long term technical relationship with partners

Proactively communicate feedback, updates, status to direct team as well as relevant cross-functional teams

Create clear and concise documentation, including technical specifications, best practices guides, and presentations, to communicate complex AI concepts to both technical and non-technical stakeholders internally and externally

Minimum Qualifications:

Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience5+ years of experience as software engineer, technical consultant or partner/sales engineer5+ years of experience in one or more of the following areas:
Deep Learning, LLMs, NLP, Speech, Conversational AI, AI-Infrastructure, Fine-tuning and optimizations of PyTorch models

Software development experience in languages like Python, Java, Go, Rust, C/C++. (at least one)

Experience with at least one LLM such as Llama, GPT, Claude, Falcon, etc

Experience with at least one deep learning framework such as PyTorch and/or JAXExperience building cloud solutions on any cloud.

Experience with Open Source cloud stacks like Kubernetes, Kubeflow, Docker containers

Experience communicating and presenting to technical and business audiences

Preferred Qualifications:

(Nice to have) Contributed to an Open Source project, submitted PRs for features/ fixed bugs and/or created sample applications in OSS or participated in Kaggle competitions

Data science background and experience manipulating/transforming data, model selection, model training, model optimization and deployment at scale(Nice to have)

Experience of launching a product / service or application into market is a plus Experience applying relevant AI and machine learning techniques to build

Experience working with internal and external partners

Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
Experience deploying production-grade machine learning solutions on public cloud platforms (like AWS)
Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality…