Meta is seeking a Partner Engineer to join Meta’s AI Partner Engineering team, a highly technical team that works with strategic partners, machine learning leaders across the industry and all major cloud service providers for building and launching new Generative AI product services and experience and taking Large Language Models (LLMs) from research to production. In this role, you will engage with some of the world's most influential companies and work closely with our Llama engineering and AI research teams. 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.
Responsibilities
AI Solution Development: Apply advanced AI and machine learning techniques to build and launch generative AI solutions using Meta’s state-of-the-art LLMs. Architect scalable, reliable, and modular solutions in collaboration with partners, leveraging Meta models for proof of concept and production deployments Technical Integration & Support: Work closely with Meta’s strategic partners on deep learning and LLM integrations. Provide advanced troubleshooting, resolve complex integration challenges, and support the deployment of production-level AI applications across cloud providers (e.g., AWS, Azure, GCP) Model Optimization & Engineering: Engage in model development, fine-tuning, evaluation, and optimization. Utilize advanced algorithms and prompt engineering to enhance model performance and ensure technical success for key solutions (e.g., Customer Care, Physical Work Supervision etc) Reference Architectures & Tooling: Develop reference architectures, technical samples, and resources for the broader Meta developer community Partner Advocacy & Product Feedback: Collect and champion partner feedback within Meta’s internal product development processes, ensuring partner needs are reflected in ongoing improvements Strategic Influence & Communication: Serve as a subject matter expert with strategic influence on partners and internal teams. Effectively plan, lead, and execute projects with minimal oversight, and proactively communicate feedback, updates, and status to direct and cross-functional teams Documentation & Evangelism: Authoring clear and concise documentation, including technical specifications, best practice guides, and presentations. Communicate complex AI concepts to both technical and non-technical stakeholders, internally and externally
Qualifications
5+ years 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 Processing, 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) Direct experience working with Large Language Models (LLMs) beyond just API interactions Experience with at least one deep learning framework such as PyTorch and/or JAX Experience 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 BS, MS or Ph.D. degree in Computer Science or related quantitative field Solid understanding of at least one Deep Learning framework (PyTorch, Tensorflow or MXNet) Experience building Deep Learning - Computer Vision or Natural Language Processing or Recommender Systems models using the frameworks Data science background and experience manipulating/transforming data, model selection, model training, model optimization and deployment at scale Experience deploying production-grade machine learning solutions on public cloud platforms (like AWS) Experience of launching a product / service or application into market is a plus Knowledge of Mobile/IoT for deploying ML models at the edge is a plus Contributed to an Open Source project, submitted PRs for features/ fixed bugs and/or created sample applications in OSS or participated in Kaggle competition Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies