Senior Specialist Solutions Engineer (ai/ml)

Databricks Databricks · Data AI · London, United Kingdom · Field Engineering - Other

Senior Specialist Solutions Engineer (AI/ML) at Databricks, focusing on guiding customers in architecting and implementing production-grade ML and GenAI applications on the Databricks platform. The role involves pre-sales technical expertise, building MVPs, deep-dive sessions, and thought leadership.

What you'd actually do

  1. Lead the architectural design of production-grade ML workloads on our unified platform, encompassing the entire MLOps lifecycle from end-to-end pipeline creation and optimization (training/inference) to seamless integration with cloud-native services.
  2. Provide advanced technical support to the Solution Architects during the technical sales cycle by building MVPs, leading deep-dive technical sessions, and strategically aligning ML/data science solutions to complex customer business challenges using relevant real-world examples.
  3. Serve as the trusted technical advisor for customers developing GenAI solutions, specializing in the design and implementation of RAG architectures on enterprise knowledge bases, enabling natural language querying of structured data, and establishing content generation and monitoring frameworks.
  4. Drive community growth and platform adoption through thought leadership activities, including the creation of technical tutorials and training materials, as well as leading hackathons and presenting at industry conferences.

Skills

Required

  • Data Science
  • Machine Learning
  • AI
  • LLM
  • GenAI
  • ML Engineering
  • Data Engineering
  • customer-facing technical expertise
  • architecting production-grade ML applications
  • MLOps lifecycle
  • training/inference pipeline optimization
  • cloud-native services integration
  • building MVPs
  • deep-dive technical sessions
  • GenAI solutions design
  • RAG architecture implementation
  • natural language querying of structured data
  • content generation and monitoring frameworks
  • thought leadership
  • technical tutorials and training materials creation
  • hackathons
  • industry conferences presentation
  • Distributed Spark based systems
  • Graduate degree in a quantitative discipline or equivalent practical experience
  • communicating and teaching technical concepts to non-technical and technical audiences

Nice to have

  • customer-facing experience in a pre-sales or post-sales role
  • Experience working with Apache Spark™ to process large-scale distributed datasets

What the JD emphasized

  • production-grade ML applications
  • GenAI solutions
  • RAG architectures
  • enterprise knowledge bases
  • content generation and monitoring frameworks

Other signals

  • customer-facing technical expert
  • architecting production-grade ML applications
  • GenAI solutions
  • RAG architectures