Solutions Engineer, Domino Data Lab
Life Sciences
$160-230k
OTE
More information about location
Enterprise AI platform
Be an early applicant
Enterprise AI platform
201-500 employees
Be an early applicant
$160-230k
OTE
More information about location
201-500 employees
Company mission
To unleash AI to address the world's most important challenges.
Role
Who you are
- A technical background — from life sciences or from a general tech/solutions environment. You've either worked inside a pharma, biotech, CRO, genomics, or medical device organization doing code-first analytical or scientific work, or you've built and supported technical solutions at a general technology or software company. Either way, you understand what it actually feels like to build and run real systems for real users, and you can translate that experience credibly in front of technical and scientific stakeholders alike
- Working knowledge of at least one life sciences domain — drug discovery, clinical development, computational biology, manufacturing/QC, or regulatory data management. Credible in front of scientific stakeholders without needing to be a domain expert
- Platform or tooling ownership experience — ideally you’ve built, operated, or meaningfully contributed to an internal platform or shared scientific computing environment. You’ve influenced or helped shape how that platform served its users, even without a formal product owner title
- Experience in a solutions engineering, pre-sales, or customer-facing technical role — or equivalent internal/consulting work where the job was diagnosing technical problems and helping others solve them, not just executing defined tasks
- You’ve led or contributed to technical evaluations, pilots, or proof-of-concepts — whether at a vendor, internally, or as a consultant — that drove meaningful adoption or investment decisions
- Demonstrated ability to build: you’ve written production or near-production code to solve a real scientific or operational problem. Experience creating internal tools, pipelines, or applications for scientific teams is a strong signal
- Proficiency in Python and/or R; hands-on experience with the data science and ML tools used in life sciences technical work. Familiarity with how models get built, validated, and moved toward production in a regulated context is a plus
What the job involves
- We help F100 Life Sciences organizations envision the full potential of our platform, guiding them from discovery to realization. Our Solutions Engineers craft compelling product demonstrations, design and execute impactful proof-of-concepts, and shape technical strategies that drive successful customer deployments
- Engage deeply with the technical problems customers are trying to solve — taking the time to genuinely understand their workflows, constraints, and frustrations before proposing anything. The goal is always to find the best solution for the customer, not to fit them to a predetermined answer
- Design and run hands-on proof-of-concept projects tailored to each customer's environment: model development for drug discovery, clinical analytics pipelines, regulatory submission workflows, omics data processing, and similar use cases
- Work with account executives to design architectures that address life sciences-specific requirements around data governance, reproducibility, and validation (e.g., 21 CFR Part 11, GxP environments)
- Proactively identify novel use cases within life sciences customers where Domino could create meaningful value — drawing on industry knowledge to surface opportunities that customers may not have considered and that go beyond the initial scope of an engagement
- Build and maintain reusable technical environments and assets that make future customer engagements faster and more substantive
- Partner with Customer Success and Solutions Architects to make sure customers who complete a POC are set up to succeed in production
- Build custom prototypes and applications on top of Domino for customers — using AI-assisted coding tools to move quickly — to demonstrate value in ways that go beyond standard demos. This reflects our directional shift toward Forward Deploy Engineering as a growing part of field work over the next 12 months
- Success is most visible when customers come away from technical engagements with a clear understanding of how Domino solves their problems — and when those engagements convert to production deployments
Our take
Domino Data Lab powers model-driven businesses with its Enterprise MLOps platform. Trusted by over 20% of the Fortune 100, Domino can accelerate the development and deployment of data science work, while simultaneously increasing collaboration and governance.
Using the platform, enterprises can develop better medicines, grow more productive crops, build better cars, and more. In 2022, it released two additional solutions that enable customers to easily run machine learning and data science workloads across hybrid and multi-cloud systems - showing that it can keep pace with the advancing needs of its clientele.
With nearly all multinational organizations set to invest in local data processing infrastructures and mitigation services by he end of 2026, Domino Data Lab is meeting the needs companies face when scaling data science workloads. It is also addressing the "data science talent gap" with its latest release, Domino Code Assist (DCA). This enables business analysts to elevate their work into the data science world and communicate with advanced data scientists in the same languages, without the need for extensive training.
Freddie
Company Specialist at Welcome to the Jungle
Insights
-16% employee growth in 12 months
Company
Funding (last 2 of 8 rounds)
Oct 2021
$100m
SERIES F
Jun 2020
$43m
LATE VC
Total funding: $226.6m
Company benefits
- Health & wellness: Premium medical, dental, and vision insurance plans, including a free option for you and your family
- Commuter benefits: What’s your transportation of choice? We support your daily commute, whether Uber, Lyft, bus, or train
- Love for parents: New parents receive up to eight weeks of fully paid-parental leave. P.S. Got baby pics? Share them in our Slack channel dedicated to kids
- Flexible paid time off: We value your right to disconnect. Take the time you need to recharge, spend time with family, and explore the world
- Annual education reimbursement: Pursue the professional growth that will help you excel in your role with educational opportunities that work for your needs, and at your speed
- Own your outcome: Feel supported to get your work done how and when you need to, regardless of your location
Company HQ
SoMa, San Francisco, CA
Leadership
Nick Elprin
(Co-Founder & CEO)Graduated from Harvard with a Master's in Computer Science. Previously worked as a Senior Application Technologist at Bridgewater Associates before co-founding Domino Data Lab in 2013.
Christopher Yang
(Co-Founder & CTO)Graduated from MIT with a Master's in Computer Science. Previously worked as a Software Developer at Bridgewater Associates before co-founding Domino Data Lab in 2013.
Thomas Robinson
(COO)Thomas joined Domino in 2016 as CPO, moving into the role of VP of Strategi Partnerships & Corporate Development in 2020 and then into the role of COO in 2022. Previously, he spent 10 years at Bridgewater Associated in various roles, including Director of Engineer and GM of Tech Talent Transformation.
Tom Gleason
(CFO)Prior to joining Domino in 2021, Tom was a VP of Finance & Strategy at Avalara. Before that, he spent 9 years at Tableau Software in various roles, including Director of Financial Planning & Analysis and VP of Finance.
Thomas Been
(CMO)Prior to joining Domino in 2023, Thomas was a CMO at DataStax and Druva. He also spent nearly 15 years at TIBCO Software in various roles, including VP of Product Management and CMO.
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