Databricks
Senior Specialist Solutions Engineer (AI/ML)
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ReqID: FEQ327R328
Job Title: Senior Specialist Solutions Engineer (SSE) – ML Engineering Recruiter: Dina Hussain Location: London, United Kingdom – Hybrid Skills Required: Data Science, Machine Learning, AI, LLM, GenAI
About the Role
As a Senior Specialist Solutions Engineer (SSE) for ML Engineering, you will act as the trusted technical ML expert for both Databricks customers and the Field Engineering team. Reporting to the Manager, Field Engineering (Specialist Team), you will:
- Collaborate with Solution Architects to help customers design, architect, and optimise production-grade ML applications on the Databricks Data Intelligence Platform.
- Continuously expand your expertise in GenAI, LLMOps, and ML, while mentoring others and establishing yourself as a thought leader in ML within the organisation.
Your role includes leading the technical direction of ML workloads, providing hands-on support during the sales process, and driving platform adoption through thought leadership.
Key Responsibilities
Your impact will be significant, spanning all aspects of the ML lifecycle:
-
Architectural Leadership
- Lead the end-to-end design of production-grade ML pipelines, from data preparation to training, optimised inference deployment, and seamless integration with cloud-native services.
- Align customer technical roadmaps with the evolving Databricks Data Intelligence Platform.
-
Customer-Facing Technical Support & Sales Alignment
- Deliver advanced technical assistance to Solution Architects during the sales cycle, including building minimum viable products (MVPs) and hosting deep-dive technical demos.
- Strategically map ML/data science solutions to complex business challenges, leveraging relevant, real-world case studies.
-
GenAI & RAG Expertise
- Serve as the trusted advisor for customers developing GenAI solutions, specialising in:
- Designing Retrieval-Augmented Generation (RAG) architectures for querying enterprise knowledge bases.
- Supporting natural language querying of structured data.
- Establishing content generation, fine-tuning strategies, and model-monitoring frameworks.
- Serve as the trusted advisor for customers developing GenAI solutions, specialising in:
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- Community & Thought Leadership
- Drive plateform adoption through:
- Creating technical tutorials and training materials.
- Leading internal hackathons and participating in industry conferences.
- Shaping Databricks’ technical narratives around GenAI, LLMOps, and ML.
- Drive plateform adoption through:
Requirements
Technical & Industry Experience Needed
- Experienced technical professional with a strong customer-facing background.
- Extensive expertise in Data Science, Machine Learning, and/or Data Engineering.
- Pre-sales, post-sales, or solution engineering experience working with external clients across diverse industry markets.
Hands-On ML & Data Expertise
You must demonstrate real-world experience in at least one of the following specialities:
- ML Engineer
- Develop production-grade cloud infrastructure (AWS/Azure/GCP) to support ML model deployment, including drift monitoring with tools like Evidently or MLflow.
- Data Scientist / NLP Specialist
- Experience with advanced NLP techniques, including vector databases (Pinecone, Weaviate, Chroma), LLM fine-tuning, and deployment frameworks like HuggingFace, LangChain, and OpenAI SDKs.
Technical Infrastructure
- Hands-on experience with distributed Spark-based systems or Databricks technologies (Delta Lake, Delta Sharing, and MLflow).
Academic Background
- Graduate degree (Master’s or PhD) in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, or related field) or
- Equivalent practical experience if lacks a degree.
Soft Skills
- Exceptional ability to communicate complex technical concepts to both non-technical and technical stakeholders.
- Passion for collaboration, lifelong learning, and driving principled innovation in ML.
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Preferred (Not Mandatory) Qualifications
- +2 years of customer-facing experience in pre-sales or post-sales technical roles.
- Experience constructing or managing enterprise-scale distributed datasets using Apache Spark or Databricks.
- Ability to meet onboarding expectations and demonstrate role-specific outcomes within 3 months.
- Willingness to travel for conferences/on-site deployments (~30% of the time).
Company Overview: Databricks
Databricks is the data and AI company, empowering over 10,000 organisations (including Comcast, Condé Nast, Grammarly, and 50% of Fortune 500 firms) to unify and democratise analytics and AI. Founded by the creators of Apache Spark™, Delta Lake, Lakehouse, and MLflow, Databricks is headquartered in San Francisco with global offices.
Benefits (Coming Soon for Your Region)
At Databricks, we strive to provide comprehensive benefits aligned with employees’ needs. Detailed information for the UK region (including Hybrid Work policies, flexible perks, and more) will be communicated upon interview.
Commitment to Diversity & Inclusion
Databricks upholds strong principles of equal employment opportunity and inclusive hiring, ensuring no discrimination based on:
- Age, colour, disability, ethnicity
- Family/marital status, gender identity/expression
- Language, national origin, physical/mental ability
- Political affinity, race, religion, sexual orientation
- Socio-economic status, veteran status, or other protected characteristics
Note on Compliance: If applicable, responsibilities involving export-controlled technology may require review by Databricks’ compliance team, including potential U.S. government license processes. This consideration applies solely at Company discretion.
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