About the company
Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks 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.
- Partner with Solutions Architects, Solutions Engineers, and Account teams to scope, design, and de-risk GenAI use cases — from retrieval-augmented generation and agentic systems to fine-tuning and evaluation.
- Build hands-on proofs of concept and reference implementations that operationalise large-scale LLM and deep learning workloads on Databricks (Mosaic AI, MLflow, Model Serving, Vector Search, Unity Catalog governance).
- Lead fine-tuning and model-customisation engagements on open LLMs (e.g., Llama-family models), including judge-based and label-efficient evaluation approaches.
- Act as a bridge to Product and Engineering — channel field and customer feedback into the roadmap.
- Enable and mentor the broader EMEA Emerging DNB Field Engineering team through workshops, reference architectures, and internal enablement.
- Represent Databricks externally as a technical thought leader — conference talks, blogs, and customer executive briefings.
Requirements
- Strong understanding of the LLM landscape, including leading proprietary and open-source models and providers.
- Deep expertise in the modern GenAI stack: LLM application patterns (RAG, agents, tool use), fine-tuning and model customization, prompt and evaluation engineering, and LLM guardrails/safety.
- Strong foundations in machine learning and deep learning, including distributed training, GPU workloads, and the full MLOps lifecycle (tracking, registry, serving, monitoring).
- Proficiency in Python and the ML ecosystem (PyTorch/Transformers, MLflow, Spark).
- Experience with the Databricks platform — or the ability to ramp on it quickly — including Mosaic AI, Model Serving, Vector Search, and Unity Catalog.
- Cloud experience across AWS, Azure, or GCP.
- Excellent communication and consultative skills.
- A track record of technical leadership and mentorship.
- Based in the United Kingdom and able to work across EMEA time zones, with willingness to travel to customer sites within the region as needed.
Conditions
- Location: United Kingdom (Remote/Hybrid — London or UK-based).
- Full-time position.
- Recruiter: Dina Hussain.
- REQ ID: FEQ227R147.