Fullstack AI Engineer - Remote

FULLSTACK AI ENGINEER – REMOTE

Overall summary:

The the is within the Machine Learning (ML) Practice team which is a highly specialized customer-facing ML team at Databricks facing an increasing demand for Large Language Model (LLM)-based solutions. We deliver professional services engagements to help our customers build, scale, and optimize ML pipelines, as well as put those pipelines into production.

We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations, as well as support internal subject matter expert (SME) teams. This team is the right fit for you if you love working with customers, teammates, and fueling your curiosity for the latest trends in LLMs, MLOps, and ML more broadly.

Your role:

• Develop LLM solutions on customer data, such as RAG architectures on enterprise knowledge repos, querying structured data with natural language, and content generation;
• Help customers solve tough problems across industries like Health and Life Sciences, Finance, Retail, Startups, and many others;
• Build, scale, and optimize customer data science workloads across industries and apply best-in-class MLOps to productionize these workloads;
• Advise data teams on data science architecture, tooling, and best practices;
• Collaborate cross-functionally with the product and engineering teams to define priorities and influence the product roadmap.

Your profile:

• Experience in building Generative AI applications, including RAG, agents, Text2SQL, fine-tuning, and deploying LLMs, using tools such as HuggingFace, Langchain, and OpenAI;

• 4+ years of hands-on industry data science experience, leveraging typical machine learning and data science tools including pandas, MLflow, scikit-learn, and PyTorch;

• Experience in building production-grade ML or GenAI deployments on AWS, Azure, or GCP;

• Experience in communicating and teaching technical concepts to both non-technical and technical audiences;

• Passion for collaboration, life-long learning, and driving business value through ML.

• One of the following languages is a huge plus: either Italian, German or Polish .