Databricks

Databricks

Posted via Greenhouse

Senior Specialist Solutions Engineer (AI/ML)

Posted Aug 5, 2026

Role at a glance

Salary
Not Disclosed
Location
United Kingdom - London
Work arrangement
Hybrid
Employment
Full-time
Experience
[Preferred] 2+ years customer-facing experience in a pre-sales or post-sales role
Education
Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent...

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Role Summary

AI-generated

The Senior Specialist Solutions Engineer, ML Engineering, serves as a technical ML expert for Databricks customers and the Field Engineering organization. The role works with Solution Architects and customers to design production-grade ML and GenAI applications on the Databricks Data Intelligence Platform, while supporting technical sales and platform adoption.

What You'll Do

  • Lead architectural design of production-grade ML workloads across the full MLOps lifecycle, including pipeline creation, optimization,...
  • Support Solution Architects during technical sales cycles by building MVPs, leading deep-dive technical sessions, and aligning ML and...
  • Advise customers on GenAI solutions, including RAG architectures, natural language querying of structured data, and content generation...
  • Create technical tutorials and training materials, lead hackathons, and present at industry conferences to drive community growth and...

Generated from the employer's posting. Verify important details before applying.

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Qualifications

Customer-facing technical experience in Data Science, Machine Learning, or Data Engineering; hands-on industry ML experience; experience with distributed Spark-based systems; experience communicating and teaching technical concepts to technical and non-technical audiences; ability to meet technical training and role-specific outcomes within 3 months of hire; ability to travel up to 30% when needed.

Required

  • Data Science, Machine Learning, or Data Engineering background
  • Pre-sales or post-sales experience working with external clients across a variety of industry markets
  • Hands-on industry ML experience in cloud infrastructure for ML applications, or natural language processing including vector databases,...
  • Hands-on experience working with Distributed Spark based systems
  • Graduate degree in a quantitative discipline or equivalent practical experience
  • Experience communicating and teaching technical concepts to non-technical and technical audiences alike
  • Can meet expectations for technical training and role-specific outcomes within 3 months of hire
  • Can travel up to 30% when needed

Preferred

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

Original job description

Content provided by the employer

ReqID: FEQ327R328

Recruiter: Kanwal Matharu

Location:  London, United Kingdom - Hybrid

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

As a Senior Specialist Solutions Engineer (SSE), 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.

You will be reporting to the Manager, Field Engineering (Specialist Team)

The impact you will have:

  • 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.
  • 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.
  • 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.
  • 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.

What we look for:

  • Experienced, technical, customer-facing, and with a background in Data Science / Machine Learning, and Data Engineering.  Looking to learn and develop in a customer-facing technical role as a subject matter expert (SME) in a pre-sales environment.
  • Pre-sales or post-sales experience working with external clients across a variety of industry markets

Data Science/ML Skills

  • 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 HuggingFace, Langchain, and OpenAI
  • Hands-on experience working with Distributed Spark based systems.
  • 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

About Databricks

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. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.

Benefits

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 click here.

Our Commitment to Diversity and Inclusion

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.

Compliance

If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.

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Databricks

About the company

Databricks

Large Enterprise

Databricks is a cloud-based data platform that specializes in providing solutions for data engineering, machine learning, and analytics. Founded in 2013 by the original creators of Apache Spark, the company enables organizations to unify data processing and analysis workflows, facilitating collaboration for data professionals. Databricks offers an integrated environment for data scientists, engineers, and business analysts, streamlining the process of building and deploying AI and data-driven applications. With a strong emphasis on simplifying big data management, Databricks helps businesses harness the power of their data to drive innovation and insights.