Job Title: Staff Software Engineer Company Name: Domino Data Lab Job Url: https://jobright.ai/jobs/search?utm_source=1012&utm_medium=google_search&utm_campaign=N_Brand_CPC_Search&utm_content=US&utm_term=jobright&gad_source=1&gad_campaignid=23563305051&gbraid=0AAAAA_SS3j4GzhP9ksTlJZzYPdBnCXul3&gclid=Cj0KCQjws83OBhD4ARIsACblj18j5nNIM2xToypuNo7sCcK5_kGkqEzisYdzwJS9Q_tvlXPRSofbYKoaAsZ4EALw_wcB&value=Software+Engineer&searchType=job_title&country=US&jobTaxonomyList=%5B%7B%22taxonomyId%22%3A%2200-00-00%22%2C%22title%22%3A%22Software+Engineer%22%7D%5D&isH1BOnly=false&excludeStaffingAgency=false&excludeSecurityClearance=false&excludeUsCitizen=false&refresh=false&position=9&sortCondition=0&seniority=3%2C4%2C5&jobTypes=1%2C2&workModel=2&daysAgo=1 Job Description: Domino Data Lab ยท 4 minutes ago Staff Software Engineer, MDLC United States Full-time Remote Lead/Staff $200K/yr - $250K/yr 94% STRONG MATCH 78% Exp. Level 100% Skill 83% Industry Exp. Domino Data Lab is a company that builds software to help AI-driven organizations operate advanced data science solutions. The Staff Software Engineer will work on the Model Development Lifecycle Team, focusing on integrating model monitoring, enhancing tagging capabilities, and expanding LLM hosting capabilities to support AI model development and deployment. Artificial Intelligence (AI) Big Data Enterprise Software Software AI Infrastructure Analytics Data Mining Enterprise Applications Machine Learning Comp. & Benefits H1B Sponsor Likely Insider Connection @Domino Data Lab 2 email credits available today Discover valuable connections within the company who might provide insights and potential referrals. Get 3x more responses when you reach out via email instead of LinkedIn. Beyond Your Network View P R K A M Pablo Rodriguez & 4 connections From Your Previous Company Unlock F F F & 2 connections Previously@undefined and... From Your School Unlock F F F & 2 connections @undefined and... Find Any Email Responsibilities 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 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 Qualification Represents the skills you have Find out how your skills align with this job's requirements. If anything seems off, you can easily click on the tags to select or unselect skills to reflect your actual expertise. Distributed Computing API Development Performance Optimization Testing CI/CD ML Model Deployment Cloud Platforms Back-End Development Required Hands-on experience developing and managing high-performance back-end systems in distributed computing environments Working closely with cross-functional teams to integrate systems with front-end interfaces and third-party services Designing and implementing secure, scalable APIs (e.g., RESTful APIs, gRPC) Profiling and optimizing back-end performance, especially in cloud environments or with container technologies like Docker and Kubernetes Using robust testing frameworks (unit, integration, end-to-end) and setting up CI/CD pipelines Familiarity with model registries, versioning, and lifecycle management tools like MLflow or KubeFlow Experience with frameworks like Apache Spark, Azure ML, or SageMaker Proficiency with cloud providers (AWS, Azure, GCP) and deploying services in these environments Expertise in languages such as Python, Java, Scala, or Go Benefits Equity Company bonus or sales commissions/bonuses 401(k) plan Medical, dental, and vision benefits Wellness stipends