
Job Overview
Location
Remote US
Job Type
Full-time
Category
Sales
Date Posted
April 21, 2026
Full Job Description
đź“‹ Description
- • As a Solutions Engineer for Life Sciences at Domino Data Lab, you will help F100 life sciences organizations unlock the full potential of the Domino platform by guiding them from discovery to production deployment of AI and data science solutions.
- • Day to day, you will engage deeply with customers to understand their technical workflows, design and run tailored proof-of-concept projects (e.g., drug discovery models, clinical analytics pipelines, omics data processing), collaborate with account executives on architectures meeting life sciences regulatory needs (e.g., 21 CFR Part 11, GxP), identify novel use cases, build reusable technical assets, partner with Customer Success and Solutions Architects for successful POC-to-production transitions, and develop custom prototypes using AI-assisted coding tools to demonstrate value beyond standard demos.
- • Domino Data Lab builds software that enables the world’s largest AI-driven organizations to develop and operate advanced data science and AI solutions at scale, serving customers like Johnson & Johnson, GSK, Bristol Myers, UBS, FINRA, and the US Navy in solving critical challenges in medicine, finance, and national security. Backed by top investors including Sequoia, Coatue, NVIDIA, and Snowflake, Domino operates with a startup spirit despite a decade in business, emphasizing innovation, collaboration, and reproducibility in AI/ML workflows.
- • In this role, you will deepen your expertise in life sciences data science workflows, gain experience in forward-deployed engineering and technical sales, strengthen your ability to translate complex scientific problems into scalable platform solutions, and contribute directly to customer success in regulated environments — positioning you at the intersection of AI innovation and life sciences impact.
Skills & Technologies
About Domino Data Lab, Inc.
Domino Data Lab provides an enterprise MLOps platform that unifies data science teams, tools, infrastructure, and workflows in a single governed environment. It automates DevOps for data science, enabling reproducible model development, scalable compute on demand, version control, collaboration, and one-click deployment with monitoring. The platform integrates with popular open-source frameworks and cloud providers, helping organizations accelerate research, reduce operational risk, and maintain compliance across the full model lifecycle.
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