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 externallyBachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience 5+ years of experience as software engineer, technical consultant or partner/sales engineer 5+ 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++. Experience with Open Source cloud stacks like Kubernetes, Kubeflow, Docker containers Experience communicating and presenting to technical and business audiences (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 improvements) Solid understanding of at least one Deep Learning framework (PyTorch, Tensorflow, Jax) Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies BS, MS or Ph.