DigitalOcean is seeking an Applied Machine Learning Engineer to lead the technical development of their first production-grade, agentic AI solutions, bringing AI models to life and demonstrating clear business value to customers by engineering building, reliable, and observable AI systems.
Requirements
- Proven experience deploying LLM/Generative AI models into production environments.
- Expertise in Python and common data science/ML libraries (e.g., PyTorch, TensorFlow, Hugging Face).
- Solid understanding of MLOps principles and experience with version control, monitoring, and scaling AI services.
- Strong background in prompt engineering, data preparation, and vector database technologies.
Responsibilities
- Design, build, and deploy end-to-end generative AI applications and agents using modern frameworks (e.g., LangChain, LlamaIndex).
- Implement and optimize Retrieval-Augmented Generation (RAG) architectures to ground models in customer-specific data.
- Establish and execute evaluation frameworks (Evals) and A/B testing methodologies to measure model performance and guard against failure modes (e.g., hallucination).
- Collaborate with the Integrations team to ensure AI solutions are seamlessly integrated into customer products and the DigitalOcean platform.
- Work with the AI Product Manager to translate customer use cases into rapid, iterative AI prototypes and production pilots.
Other
- 5+ years of experience as an ML Engineer, Applied Scientist, or Software Engineer specializing in AI/ML.
- A portfolio or track record of translating cutting-edge models into tangible, applied business solutions.
- This is a remote role
- We value winning together—while learning, having fun, and making a profound difference for the dreamers and builders in the world.
- You will be a founding technical member of the AI Modernization charter
