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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Engineer - **Company:** The Lilly Company - **Location:** San Francisco, CA, United States (Remote available) - **Experience:** Experienced - **Salary:** $141,000.0 - $253,000.0 - **Contract:** Permanent contract - **Skills:** JavaScript (Programming Language), Artificial Intelligence, Amazon Web Services, Microsoft Azure, C++ (Programming Language), Computer Clusters, Software Quality, Nvidia CUDA, Distributed Computing Environment, Python (Programming Language), Machine Learning, Node.Js, NumPy, Azure Machine Learning, SciPy, Systems Architecture, Data Processing, Pytorch, ReactJS, Large Language Models, Backend, Pandas, Containerization, Kubernetes, Information Technology, Slurm, Machine Learning Operations, Front End Software Development, TensorRT, Hardware Infrastructure, Api Design, Docker - **Published:** September 15, 2026 - **Apply:** https://dejobs.org/x/x/739AD01FE0714363A6B402ED5CFCEF75/job/ ## About the Role * Advanced Python with production experience in PyTorch or JAX, and a track record of taking machine learning models from research code to working systems. * Hands-on distributed training on multi-GPU, multi-node infrastructure (DDP, FSDP, DeepSpeed, or Megatron), with GPU performance profiling and optimization. * Experience optimizing and serving models for inference (Triton, vLLM, or TensorRT-LLM) with containerization and scheduling (Docker, Kubernetes, Ray, or Slurm). * Experience building evaluation and benchmarking for models - including designing the tests that reveal where a model fails, not only where it succeeds. * Full stack capability - a backend language, front-end familiarity (JavaScript with a framework such as React), and API design - enough to build the interfaces through which scientists actually use a model. * Comfort with the scientific Python stack (NumPy, SciPy, Pandas); C++ or CUDA for performance-critical work is a strong plus. * Experience with cloud AI/ML platforms (AWS, Azure, or GCP) alongside on-premises GPU clusters. * Excellent problem-solving skills and the ability to navigate ambiguity in a highly technical environment. * Strong written and verbal communication and demonstrated ability to partner well with research scientists. * Experience with distributed training or large-scale model deployment on GPU infrastructure. * Prior experience working across the full stack of an AI application - data, model, service, and interface. Your Basic Qualifications * Master's degree in Computer Science, Machine Learning, Artificial Intelligence, Data Science, Engineering, or a related technical field . * 4+ years of hands-on engineering experience building machine learning systems, including taking models from research or prototype into real working use. ## Description As an AI Engineer, you will turn advanced AI models into reliable tools that support drug discovery. You will build, train, evaluate, and deploy AI systems, working closely with AI Scientists to shape model design and technical decisions. This is a hands-on role with opportunities to contribute to both engineering and scientific innovation. You'll collaborate with AI Scientists, ML Ops Engineers, Data Engineers, and NVIDIA experts to develop cutting-edge AI solutions. How You'll Succeed * AI and Automation Execution: Develop and apply innovative AI techniques to solve complex business challenges, creating tailored solutions that drive strategic value and transform clinical research processes that support AI scientists. * Full Stack Development: Build and implement AI-driven models and applications across the full stack, from backend services to frontend interfaces. * System Architecture and Design: Design and uphold resilient system architectures to guarantee optimal performance, scalability, and security across all platforms. * Handle large scale model development. * Cross-Disciplinary and Organization Collaboration: Effectively engage with colleagues to gather innovative ideas and insights, fostering a collaborative environment that inspires and motivates team members to innovate and explore creative solutions in AI development. * Ethics and Compliance in Development: Adhere to ethical guidelines in AI usage and data handling, ensuring compliance with all relevant regulations and maintaining the highest standards of data privacy and security. * Elevate engineering excellence through architecture reviews, code quality leadership, and mentorship, while safeguarding Lilly's proprietary data, models, and intellectual property. ## Related Videos - [Python Data Visualization @ Deepnote (w/ PyViz overview)](https://www.wearedevelopers.com/videos/113-python-data-visualization-deepnote-w-pyviz-overview) - [Running Secure Life Science Research at Scale using Hybrid GPU HPC and Kubernetes 🧬](https://www.wearedevelopers.com/videos/100355-running-secure-life-science-research-at-scale-using-hybrid-gpu-hpc-and-kubernetes) - [Developer Experience, Platform Engineering and AI powered Apps](https://www.wearedevelopers.com/videos/990-developer-experience-platform-engineering-and-ai-powered-apps) - [Vectorize all the things! 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