{"schemaVersion":"jobsearcher.job.v1","id":"ccf3b462455f3150585edce7","url":"https://jobsearcher.com/jobs/ccf3b462455f3150585edce7","canonicalUrl":"https://jobsearcher.com/jobs/ccf3b462455f3150585edce7","title":"Senior Machine Learning Engineer","description":"Our client is transforming grocery shopping by giving people time back — shoppers handpick fresh groceries and household essentials and deliver them in as little as one hour. We're hiring a Senior Machine Learning Engineer for our Personalization Platform team within the Membership organization. You'll partner closely with Data Scientists to design, deploy, and scale personalized recommendation and ranking models that drive engagement across the Shipt marketplace. This is a hands-on senior technical role spanning architecture, ML infrastructure, and production systems — from training and serving pipelines to CI/CD and monitoring. If you have an AI-first mindset and enjoy building platforms that make other engineers and scientists more effective, this is your team.\n\nResponsibilities\n\nPartner with Data Scientists, Product Managers, and peer engineering teams to build and ship AI product features\nDesign, build, and maintain scalable ML infrastructure and production systems, including batch and streaming data pipelines for model training and serving\nDeploy, serve, and monitor models in public cloud environments via microservices that meet throughput and latency requirements\nDefine best practices for AI product development: pipeline automation, model versioning, deployment, and scalable serving\nDesign and manage CI/CD pipelines for machine learning deployments\nIntegrate models into search and ranking systems (e.g., Elasticsearch first-stage retrieval and downstream ranking services)\nOwn accountability for the implementation of AI product features end to end\nUse modern monitoring and telemetry tooling to identify, assess, and prioritize platform issues\nSupport experimentation and A/B testing infrastructure, offline evaluation harnesses, and search-quality reporting\nStay current on emerging AI/ML technology and bring the best of it to the team\n\nRequirements\n\nMS or PhD in Computer Science, Engineering, Mathematics, or equivalent practical experience.\n5+ years in machine learning and backend software engineering.\nStrong proficiency in Python, plus at least one other backend language (Go or Java preferred).\nDeep understanding of user modeling, embeddings, similarity search, and ranking models.\nStrong experience with serving architectures (REST/gRPC APIs, model servers) and low-latency inference.\nHands-on experience with modern AI development tooling — MCP servers/clients, PydanticAI, LangGraph, LiteLLM, or similar.\nExperience with ML pipeline and experiment-tracking tools (MLflow, Kubeflow, Airflow, Weights & Biases, or similar).\nSolid grasp of distributed systems, microservices, and system design.\nCloud experience (AWS, GCP, or Azure) and containerized development (Docker, Kubernetes).\nExperience with SQL and NoSQL databases and large-scale datasets.\nFamiliarity with the full data science workflow — data ingestion, feature engineering, experimentation, deployment, and monitoring.\nExposure to experimentation platforms and online A/B testing.\nStrong written and verbal communication; able to explain ML results and applications to scientists, engineers, and business partners\n\nWe offer\n\nOpportunity to work on cutting-edge projects\nWork with a highly motivated and dedicated team\nCompetitive salary\nFlexible schedule\nBenefits package - medical insurance, vision, dental, etc.\nCorporate social events\nProfessional development opportunities\nWell-equipped office\nPlease note that all onboardings must occur in person and you may be asked to travel to attend.\n\nAbout us\nGrid Dynamics (NASDAQ: GDYN) is a leading provider of technology consulting, platform and product engineering, AI, and advanced analytics services. Fusing technical vision with business acumen, we solve the most pressing technical challenges and enable positive business outcomes for enterprise companies undergoing business transformation. A key differentiator for Grid Dynamics is our 8 years of experience and leadership in enterprise AI, supported by profound expertise and ongoing investment in data, analytics, cloud & DevOps, application modernization and customer experience. Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.","company":"Griddynamics","rawCompany":"griddynamics","city":"Denver","state":"CO","isRemote":false,"isActive":false,"createdAt":"2026-08-15T13:34:18.278Z","occupations":[{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"}],"industries":[{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Senior Machine Learning Engineer","description":"Our client is transforming grocery shopping by giving people time back — shoppers handpick fresh groceries and household essentials and deliver them in as little as one hour. We're hiring a Senior Machine Learning Engineer for our Personalization Platform team within the Membership organization. You'll partner closely with Data Scientists to design, deploy, and scale personalized recommendation and ranking models that drive engagement across the Shipt marketplace. This is a hands-on senior technical role spanning architecture, ML infrastructure, and production systems — from training and serving pipelines to CI/CD and monitoring. If you have an AI-first mindset and enjoy building platforms that make other engineers and scientists more effective, this is your team.\n\nResponsibilities\n\nPartner with Data Scientists, Product Managers, and peer engineering teams to build and ship AI product features\nDesign, build, and maintain scalable ML infrastructure and production systems, including batch and streaming data pipelines for model training and serving\nDeploy, serve, and monitor models in public cloud environments via microservices that meet throughput and latency requirements\nDefine best practices for AI product development: pipeline automation, model versioning, deployment, and scalable serving\nDesign and manage CI/CD pipelines for machine learning deployments\nIntegrate models into search and ranking systems (e.g., Elasticsearch first-stage retrieval and downstream ranking services)\nOwn accountability for the implementation of AI product features end to end\nUse modern monitoring and telemetry tooling to identify, assess, and prioritize platform issues\nSupport experimentation and A/B testing infrastructure, offline evaluation harnesses, and search-quality reporting\nStay current on emerging AI/ML technology and bring the best of it to the team\n\nRequirements\n\nMS or PhD in Computer Science, Engineering, Mathematics, or equivalent practical experience.\n5+ years in machine learning and backend software engineering.\nStrong proficiency in Python, plus at least one other backend language (Go or Java preferred).\nDeep understanding of user modeling, embeddings, similarity search, and ranking models.\nStrong experience with serving architectures (REST/gRPC APIs, model servers) and low-latency inference.\nHands-on experience with modern AI development tooling — MCP servers/clients, PydanticAI, LangGraph, LiteLLM, or similar.\nExperience with ML pipeline and experiment-tracking tools (MLflow, Kubeflow, Airflow, Weights & Biases, or similar).\nSolid grasp of distributed systems, microservices, and system design.\nCloud experience (AWS, GCP, or Azure) and containerized development (Docker, Kubernetes).\nExperience with SQL and NoSQL databases and large-scale datasets.\nFamiliarity with the full data science workflow — data ingestion, feature engineering, experimentation, deployment, and monitoring.\nExposure to experimentation platforms and online A/B testing.\nStrong written and verbal communication; able to explain ML results and applications to scientists, engineers, and business partners\n\nWe offer\n\nOpportunity to work on cutting-edge projects\nWork with a highly motivated and dedicated team\nCompetitive salary\nFlexible schedule\nBenefits package - medical insurance, vision, dental, etc.\nCorporate social events\nProfessional development opportunities\nWell-equipped office\nPlease note that all onboardings must occur in person and you may be asked to travel to attend.\n\nAbout us\nGrid Dynamics (NASDAQ: GDYN) is a leading provider of technology consulting, platform and product engineering, AI, and advanced analytics services. Fusing technical vision with business acumen, we solve the most pressing technical challenges and enable positive business outcomes for enterprise companies undergoing business transformation. A key differentiator for Grid Dynamics is our 8 years of experience and leadership in enterprise AI, supported by profound expertise and ongoing investment in data, analytics, cloud & DevOps, application modernization and customer experience. Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.","datePosted":"2026-08-15T13:34:18.278Z","dateModified":"2026-08-15T13:34:18.278Z","hiringOrganization":{"@type":"Organization","name":"Griddynamics","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Denver","addressRegion":"CO","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"ccf3b462455f3150585edce7"},"url":"https://jobsearcher.com/jobs/ccf3b462455f3150585edce7"}}