What we are buildingThe 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 beIn your first year, you will:
- Build and enhance platform features that enable teams to design, test, and deploy multi-agent workflows at scale.
- Enhance Domino's Extensions framework for enabling customers to build custom modules that extend platform feature and function
- Expand the platform's inference infrastructure to support high-throughput, low-latency serving of large language models, helping customers confidently operationalize LLM applications at enterprise scale.
What we look for in this 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
- Familiarity with traditional machine learning model development and AI workflows, including experiment tracking, hyperparameter optimization, model evaluation frameworks, and managing model artifacts
- 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
- Back-End Development: Expertise in languages such as Python, Java, Scala, or Go
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.
Compensation Range
$200,000-$250,000 USD
