Staff Software Engineer, Domino Data Lab
Model Development Lifecycle Team
$200-235k
Data science & AI platform
Open for applications
Data science & AI platform
201-500 employees
Open for applications
$200-235k
201-500 employees
Company mission
To unleash the power of data science to address the world's most important challenges.
Role
Who you are
- 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
- 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
What the job involves
- 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
- 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
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 is able to 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 2026, Domino Data Lab is making an early start on 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
Company
Funding (last 2 of 8 rounds)
Oct 2021
$100m
SERIES F
Jun 2020
$43m
LATE VC
Total funding: $226.6m
Company benefits
- Premium medical, dental, and vision insurance plans, including a free option for you and your family
- Commuter benefits - we support your daily commute, whether Uber, Lyft, bus, or train
- Up to eight weeks of fully paid parental leave
- Flexible PTO
- Annual education reimbursement
- Support to get your work done how and when you need to, regardless of your location
Company HQ
SoMa, San Francisco, CA
Articles
Leadership
Nick Elprin
(CEO)Graduated from Harvard with a Master's in Computer Science. Previously worked as a Senior Application Technologist at Bridgewater Associates.
Christopher Yang
(CTO)Graduated from MIT with a Master's in Computer Science. Previously worked as a Software Developer at Bridgewater Associates.
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