Staff Software Engineer, Model Development Lifecycle Team

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
• Strong Background in AI/ML: Extensive experience or knowledge in designing, building, and deploying artificial intelligence and/or machine learning models, with a deep understanding of model development, training, optimization, and lifecycle management. Proficient in leveraging advanced tools, frameworks, and platforms to create scalable AI/ML solutions that drive impactful outcomes. Skilled in applying state-of-the-art algorithms and techniques to solve complex problems across diverse domains.
• 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
• 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

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