Who we are
At Domino, we build software that helps the largest, AI-driven organizations build and operate advanced data science and AI solutions at scale. Our platform integrates a streamlined model development environment, MLOps capabilities, and novel features for collaboration, reuse, and reproducibility — all of which make data science teams more productive, reduce time to value, and ensure compliance. Our customers — like Johnson & Johnson, GSK, Bristol Myers, UBS, FINRA and the US Navy — are using our software to solve some of the most important challenges in the world, such as developing new medicines, securing our financial markets, or protecting our country. Backed by Sequoia Capital, Coatue Management, NVIDIA, Snowflake and other leading investors, we have been in business for a decade but are still a small team operating with the spirit of a startup. Especially in the world of AI today, we believe that the future is still being invented — and we want to be the ones building it. For more information, visit www.domino.ai
What we are building
Domino's Federal Forward Deployed Engineers are the technical force behind how the US Government's most demanding AI programmes actually get built. They work directly inside customer environments, hands-on with data science and ML teams, building and deploying models on Domino where the output has real operational consequence.
These engineers are deep in the stack, standing up LLM inference endpoints in air-gapped environments, architecting MLOps workflows for DoD compliance, and building custom applications that Federal teams depend on. They operate where model development meets mission-critical infrastructure, and they're expected to bring genuine ML and data science depth to every engagement.
The role also carries weight internally. What Federal FDEs encounter in the field; the constraints, the gaps, the frontier use-cases, directly shapes how Domino's platform evolves for the public sector.
What your impact will be
- Design and build custom ML solutions and applications directly on Domino, working hands-on with Federal data science teams to accelerate how they build, train, and deploy models in mission-critical environments.
- Deploy and operationalise LLMs and other frontier models to inference endpoints within highly secured, air-gapped infrastructure, solving real constraints that most ML engineers never encounter.
- Architect and implement end-to-end MLOps workflows on Domino, covering model development, compute orchestration, versioning, reproducibility, and audit-readiness for DoD and Federal compliance requirements.
- Build reusable, production-grade assets, reference architectures, accelerators, and deployment patterns, that raise the baseline of what Federal customers can achieve on the platform and feed directly into how Domino evolves.
- Serve as the technical voice of the customer internally, translating field experience from classified and complex environments into concrete product feedback that shapes platform direction.
What we look for in this role
- 5+ years in a hands-on technical role working directly with customers, post-sales professional services, solution engineering, or embedded consulting, with a track record of delivering in complex, high-stakes environments
- Production-level Python skills with the ability to build, not just prototype; you're comfortable owning code that customers depend on
- Hands-on experience building, training, and deploying ML models, including working knowledge of the full model development lifecycle from experimentation through to inference
- Practical experience with LLM deployment, including standing up and optimising inference endpoints, ideally in constrained or regulated environments
- Comfortable operating in air-gapped or classified infrastructure; existing clearance preferred, though transfer or sponsorship is available
- Familiarity with MLOps tooling and workflows, compute orchestration, model versioning, reproducibility, and experiment tracking
- Strong technical communication skills, able to run structured discovery with data science teams and translate complex requirements into buildable solutions
- Experience running or supporting ML inference benchmarks and evaluating model performance at deployment
What we value
- We strongly believe in the value of growing a diverse team and encourage people of all backgrounds, genders, ethnicities, abilities, and sexual orientations to apply
- We value a growth mindset. High-performing creative individuals who dig into problems and see the opportunities for success
- We believe in individuals who seek truth and speak the truth and can be their whole selves at work
- We value all of you that believe improving is always possible. At Domino, everything is a work in progress – we can do better at everything
- We emphasize an environment of teaching and learning to equip employees with the tools needed to be successful in their function and the company
#LI-Remote
The annual US base salary range for this role is listed below. For sales roles, the range provided is the role's On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. This salary range will be narrowed during the interview process based on a number of factors, including the candidate's experience, qualifications, and location. Additional benefits for this role may include: equity, company bonus or sales commissions/bonuses; 401(k) plan; medical, dental, and vision benefits; and wellness stipends.
Skills Required
- 5-10+ years professional experience in customer facing technical role
- Strong customer-facing communication skills
- Technical ability to create production ready code (Python)
- Ability to script and prototype as needed
- Experience running or supporting benchmarks for ML inference deployments
What We Do
Domino Data Lab powers model-driven businesses with its leading Enterprise AI platform trusted by over 20% of the Fortune 100. Domino accelerates the development and deployment of data science work while increasing collaboration and governance. With Domino, enterprises worldwide can develop better medicines, grow more productive crops, build better cars, and much more. Founded in 2013, Domino is backed by Coatue Management, Great Hill Partners, Highland Capital, Sequoia Capital and other leading investors. For more information, visit www.domino.ai
Why Work With Us
We’re looking for sharp, scrappy people who crave a high degree of ownership, are laser-focused on personal growth, and can stick the landing between high standards and low ego. In our fast-paced environment, you’ll find all the white space and opportunity you need to thrive.
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Domino Data Lab Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.



