About Databricks
Databricks is a Data and AI company. More than 20,000 organizations worldwide rely on its Data + AI Platform to build and scale data and AI apps, analytics, and agents.
Responsibilities
•Serve as the deep technical authority on Generative AI, LLMs, and applied machine learning for the EMEA Emerging DNB business unit, supporting strategic and complex customer engagements
•Partner with Solutions Architects, Solutions Engineers, and Account teams to scope, design, and de-risk GenAI use cases, including RAG, agentic systems, fine-tuning, and evaluation
•Build hands-on proofs of concept and reference implementations for large-scale LLM and deep learning workloads on Databricks
•Lead fine-tuning and model-customization engagements on open LLMs, including judge-based and label-efficient evaluation approaches
•Channel field and customer feedback into the product roadmap and represent the roadmap to the field
•Enable and mentor the EMEA Emerging DNB Field Engineering team through workshops, reference architectures, and internal enablement
•Represent Databricks externally through conference talks, blogs, and customer executive briefings
Requirements
•Strong understanding of proprietary and open-source LLMs, their capabilities, trade-offs, and suitability for different use cases
•Deep expertise in GenAI application patterns, fine-tuning, model customization, prompt and evaluation engineering, and LLM guardrails and safety
•Strong foundations in machine learning and deep learning, including distributed training, GPU workloads, and the MLOps lifecycle
•Proficiency in Python and the ML ecosystem, including PyTorch, Transformers, MLflow, and Spark
•Experience with Databricks or ability to ramp up quickly; experience with AWS, Azure, or GCP
•Excellent communication and consultative skills, including explaining complex GenAI trade-offs to engineers and senior technical executives
•Track record of technical leadership and mentorship
•Comfortable working at the pace of digital-native and high-growth customers
•Based in the United Kingdom and able to work across EMEA time zones; willing to travel to customer sites in the region as needed
Nice to have
•Experience helping digital-native customers build data and ML solutions
•Public technical presence through conference speaking, published talks, blogs, or open-source contributions in ML/GenAI
•Domain expertise in regulated or high-stakes industries
•Experience partnering with Product and Engineering teams to influence roadmaps
Conditions
•Location: United Kingdom
•Benefits and perks are provided; specific details depend on the region
•Salary not specified
