Staff Software Engineer, MDLC

🕒 April 7

🇺🇸 United States – Remote

💵 $200k - $250k / year

⏰ Full Time

🔴 Lead

🧑‍💻 Full-stack Engineer

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Domino Data Lab

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2013

🤖 Artificial Intelligence

🏢 Enterprise

☁️ SaaS

💰 Series F on 2022-06

Artificial Intelligence • Enterprise • SaaS

Domino Data Lab is a company that empowers AI-driven enterprises to build and manage AI at scale through its Enterprise AI Platform. The platform provides an integrated experience for model development, MLOps, collaboration, and governance, enabling global enterprises to innovate across various sectors. Domino supports better medicinal development, productive agriculture, and competitive product creation. Established in 2013 and backed by notable investors like Sequoia Capital and NVIDIA, Domino enables companies to optimize AI deployment effectively.

📋 Description

• 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 • Innovate within our Domino Apps offering by incorporating feature requests from major customers

🎯 Requirements

• 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 • Back-End Development: Expertise in languages such as Python, Java, Scala, or Go

🏖️ Benefits

• equity • company bonus • 401(k) plan • medical, dental, and vision benefits • wellness stipends