Description:

Meta is looking for an experienced Partner Engineer, Generative AI to join its AI Partner Engineering team. This role offers an exciting opportunity to work with leading technology companies, cloud providers, and AI innovators to build and deploy next-generation Generative AI solutions using Meta's Large Language Models (LLMs), including Llama.

As a Partner Engineer, you will collaborate with strategic partners and Meta's AI research and engineering teams to design, optimize, and deploy scalable AI solutions. You will help partners move AI projects from proof-of-concept to production while developing technical resources such as reference architectures, case studies, technical documentation, and best-practice guides.

This position is ideal for professionals who are passionate about Generative AI, Machine Learning, Deep Learning, Cloud Technologies, and building production-ready AI systems that create real-world impact.

Key Technical Skills:

Generative AI, Large Language Models (LLMs), Deep Learning, Machine Learning, NLP, Conversational AI, Speech Processing, PyTorch, JAX, TensorFlow, Python, Java, Go, Rust, C++, Kubernetes, Kubeflow, Docker, AWS, Azure, Google Cloud Platform (GCP), Prompt Engineering, Model Fine-Tuning, AI Infrastructure, Cloud Architecture, Data Science, MLOps, Model Optimization, Open Source Technologies

Requirements:

• 5+ years of experience as a Software Engineer, Technical Consultant, Partner Engineer, or Sales Engineer.
• Hands-on experience working with Large Language Models (LLMs) beyond API integrations.
• Strong experience in Deep Learning, NLP, Conversational AI, AI Infrastructure, or related AI domains.
• Proficiency in at least one programming language such as Python, Java, Go, Rust, or C++.
• Experience with deep learning frameworks such as PyTorch or JAX.
• Knowledge of cloud platforms including AWS, Azure, or GCP.
• Experience working with containerization and orchestration technologies such as Docker and Kubernetes.
• Strong communication and stakeholder management skills.
• Ability to design scalable AI solutions and support enterprise-level deployments.
• Bachelor's, Master's, or PhD in Computer Science or a related quantitative field is preferred.
• Experience with model training, optimization, deployment, and MLOps practices is an advantage.
• Knowledge of responsible AI practices, prompt engineering, and AI workflow optimization is highly desirable.
• Open-source contributions, Kaggle participation, or product launch experience will be considered a plus.