Senior Specialist Solutions Architect - DS​/ML​/AI​/GenAI

Req: FEQ
127R163

Location:
London

Skills:
Data Science, Machine Learning, AI, LLM, GenAI

As a Senior Specialist Solutions Architect (Srv SSA) - ML Engineering, you will be the trusted technical ML expert to both Databricks customers and the Field Engineering organisation. You will work with Solution Architects to guide customers in architecting production‑grade ML applications on Databricks, while aligning their technical roadmap with the evolving Databricks Data Intelligence Platform. You will continue to strengthen your technical skills through applying the latest technologies in GenAI, LLMOps, and ML, while expanding your impact through mentorship and establishing yourself as an ML expert.

• Architect production‑level ML workloads for customers using our unified platform, including end‑to‑end ML pipelines, training/inference optimisation, integration with cloud‑native services and MLOps
• Provide advanced technical support to Solution Architects during the technical sale, ranging from feature engineering, training, tracking, serving to model monitoring, all within a single platform, and participating in the larger ML SME community in Databricks
• Collaborate with the product and engineering teams to represent the voice of the customer, define priorities and influence the product roadmap, helping with the adoption of Databricks’ ML offerings
• Build and increase customer data science workloads and apply the best MLOps to product ionise these workloads across a variety of domains
• Serve as the trusted technical advisor for customers developing GenAI solutions, such as RAG architectures on enterprise knowledge repos, querying structured data with natural language, content generation, and monitoring

• 5+ years of experience in a customer‑facing technical role. Pre‑sales or post‑sales experience working with external clients across a variety of industry markets

• 5+ years of hands‑on industry ML experience in at least one of the following:
  • ML Engineer:
    Develop production‑grade cloud (AWS/Azure/GCP) infrastructure that supports the deployment of ML applications, including drift monitoring
  • Data Scientist:
    Experience with the latest techniques in natural language processing including vector databases, fine‑tuning LLMs, and deploying LLMs with tools such as Hugging Face, Langchain, and OpenAI
• Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience
• Experience communicating and teaching technical concepts to non‑technical and technical audiences alike
• Passion for collaboration, life‑long learning, and driving our values through ML
• [Preferred] 2+ years customer‑facing experience in a pre‑sales or post‑sales role
• [Preferred] Experience working with Apache Spark™ to process large‑scale distributed datasets
• Can meet expectations for technical training and role‑specific outcomes within 3 months of hire
• Can travel up to 30% when needed

Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow.

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At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region, please visit

At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio‑economic status, veteran status, and other protected characteristics.

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