Who we are
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
What we are building
The Model Development Lifecycle Team is building a cutting-edge platform to simplify the entire machine learning journey. From development and training to deployment and management, we empower teams to turn data into actionable insights. Our platform supports:
- Seamless API Integration: Deploy models as APIs for consistent use across applications, whether on-premises, in enterprise infrastructures, or through third-party hosting
- Collaboration and Discoverability: Use our model registry to version, store, and easily find models across the organization
- Scalable Training Resources: Leverage advanced tools like GPUs, Ray, and Spark to meet the needs of diverse AI projects
By supporting organizations in developing, registering, and scaling AI models, we enable impactful insights and innovation across the enterprise.
What your impact will be
In your first year, you will
- Collaborate with customers to design solutions for deploying models to platforms like AWS SageMaker and Azure ML
- Introduce a “Data Science Catalog” for discovering and summarizing global data science resources within Domino
- Integrate model monitoring to provide a holistic view of deployment health and performance
- Enhance tagging capabilities across Domino entities to improve discoverability and tracking
- Expand LLM hosting capabilities to address customer needs for scale, performance, and logging
What we look for in this role
- 8+ years previously in a software engineering individual contributor role
- Building Scalable Systems: Hands-on experience developing and managing high-performance back-end systems in distributed computing environments
- Collaboration Across Teams: Working closely with cross-functional teams to integrate systems with front-end interfaces and third-party services
- API Development: Designing and implementing secure, scalable APIs (e.g., RESTful APIs, gRPC)
- Performance Optimization: Profiling and optimizing back-end performance, especially in cloud environments or with container technologies like Docker and Kubernetes
- Testing and CI/CD: Using robust testing frameworks (unit, integration, end-to-end) and setting up CI/CD pipelines
- ML Model Deployment: Familiarity with model registries, versioning, and lifecycle management tools like MLflow or KubeFlow is a big plus
- Distributed Computing: Experience with frameworks like Apache Spark, Azure ML, or SageMaker is a plus
- Cloud Platforms: Proficiency with cloud providers (AWS, Azure, GCP) and deploying services in these environments
What we value
- 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
- 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
#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.
0 applies
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