Asks for

The ad says“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.”
The ad says“API Development: Designing and implementing secure, scalable APIs (e.g., RESTful APIs, gRPC)”
The ad says“Cloud Platforms: Proficiency with cloud providers (AWS, Azure, GCP) and deploying services in these environments”
The ad says“Cloud Platforms: Proficiency with cloud providers (AWS, Azure, GCP) and deploying services in these environments”
The ad says“Testing and CI/CD: Using robust testing frameworks (unit, integration, end-to-end) and setting up CI/CD pipelines”
The ad says“Building Scalable Systems: Hands-on experience developing and managing high-performance back-end systems in distributed computing environments”
The ad says“Performance Optimization: Profiling and optimizing back-end performance, especially in cloud environments or with container technologies like Docker and Kubernetes”
The ad says“Cloud Platforms: Proficiency with cloud providers (AWS, Azure, GCP) and deploying services in these environments”
The ad says“API Development: Designing and implementing secure, scalable APIs (e.g., RESTful APIs, gRPC)”
The ad says“Performance Optimization: Profiling and optimizing back-end performance, especially in cloud environments or with container technologies like Docker and Kubernetes”
The ad says“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.”
The ad says“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.”
The ad says“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.”
The ad says“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.”
The ad says“Performance Optimization: Profiling and optimizing back-end performance, especially in cloud environments or with container technologies like Docker and Kubernetes”
The ad says“API Development: Designing and implementing secure, scalable APIs (e.g., RESTful APIs, gRPC)”
The ad says“Testing and CI/CD: Using robust testing frameworks (unit, integration, end-to-end) and setting up CI/CD pipelines”

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

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

#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—$235,000 USD

Asks for

Values