Databricks

4 weeks ago

Senior Specialist Solutions Engineer (AI/ML)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 1 hour agoStatus: Live

Job Summary

Senior Specialist Solutions Engineer (AI/ML) will act as the trusted ML technical expert for Databricks customers and Field Engineering, guiding production-grade ML applications on the Databricks platform, supporting pre-sales with MVPs, and shaping ML/data science solutions. You’ll mentor teams, work across GenAI/LLMOps, and lead ML architectures from training to inference in a hybrid London-based role.

Location: London

Workplace: Hybrid

Employment Type: Full time

Job Function: Solutions Engineering & Sales Engineering

Seniority: Sr. Manager level

Key Responsibilities

•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 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
•Mentor and develop the Field Engineering Specialist Team to scale ML expertise across customer engagements

Travel: Medium travel

Key Requirements

•Background in Data Science, Machine Learning, and Data Engineering; comfortable in a customer-facing technical role as SME in pre-sales environment
•Pre-sales or post-sales experience working with external clients across various industries
•Hands-on ML experience in production-grade cloud infrastructure (AWS/Azure/GCP) and ML deployment including drift monitoring; NLP techniques with vector databases, fine-tuning LLMs, and deployment tools (HuggingFace, LangChain, OpenAI)
•Hands-on experience with distributed Apache Spark-based systems
•Graduate degree in a quantitative discipline (or equivalent practical experience) and ability to teach/communicate technical concepts to diverse audiences

Experience:Data ScienceMachine LearningData EngineeringSparkCloud

Education:Master's

Skills:CommunicationPresentationMentorshipProblem-solvingCollaboration

Languages:English

Tech Stack:PythonSparkHuggingFaceLangChainOpenAIAWSAzureGCPLLMOps

Company Brief

Databricks

Provides a unified data analytics platform powered by Apache Spark to simplify building, deploying, and scaling data engineering, data science, and machine learning workloads for enterprises.

Industry: Data Infrastructure

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Scaleup

Valuation: Unicorn (USD 1B+)

Funding: Series E+

Headquarters: San Francisco, United States

Founded: 2013

Website LinkedIn

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Databricks

4 weeks ago

Senior Specialist Solutions Engineer (AI/ML)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 1 hour agoStatus: Live

Job Summary

Location: London

Workplace: Hybrid

Employment Type: Full time

Job Function: Solutions Engineering & Sales Engineering

Seniority: Sr. Manager level

Key Responsibilities

•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 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
•Mentor and develop the Field Engineering Specialist Team to scale ML expertise across customer engagements

Travel: Medium travel

Key Requirements

•Background in Data Science, Machine Learning, and Data Engineering; comfortable in a customer-facing technical role as SME in pre-sales environment
•Pre-sales or post-sales experience working with external clients across various industries
•Hands-on ML experience in production-grade cloud infrastructure (AWS/Azure/GCP) and ML deployment including drift monitoring; NLP techniques with vector databases, fine-tuning LLMs, and deployment tools (HuggingFace, LangChain, OpenAI)
•Hands-on experience with distributed Apache Spark-based systems
•Graduate degree in a quantitative discipline (or equivalent practical experience) and ability to teach/communicate technical concepts to diverse audiences

Experience:Data ScienceMachine LearningData EngineeringSparkCloud

Education:Master's

Skills:CommunicationPresentationMentorshipProblem-solvingCollaboration

Languages:English

Tech Stack:PythonSparkHuggingFaceLangChainOpenAIAWSAzureGCPLLMOps

Company Brief

Databricks

Provides a unified data analytics platform powered by Apache Spark to simplify building, deploying, and scaling data engineering, data science, and machine learning workloads for enterprises.

Industry: Data Infrastructure

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Scaleup

Valuation: Unicorn (USD 1B+)

Funding: Series E+

Headquarters: San Francisco, United States

Founded: 2013

Website LinkedIn