{"schemaVersion":"jobsearcher.job.v1","id":"377850bf60ea8faa12b2df5e","url":"https://jobsearcher.com/jobs/377850bf60ea8faa12b2df5e","canonicalUrl":"https://jobsearcher.com/jobs/377850bf60ea8faa12b2df5e","title":"Machine Learning Engineer","description":"About The RoleThe Machine Learning Engineer owns the full lifecycle of production ML systems, from data preparation and model development through deployment, monitoring, and iteration. The work spans supervised learning, ranking, forecasting, and NLP use cases where accuracy, inference latency, and operational reliability all matter.Based in Denver, CO with a remote work structure, the role partners with data scientists, software engineers, and platform teams to turn research prototypes into dependable services. The team uses Python, PyTorch or scikit-learn, cloud infrastructure, and modern MLOps practices to deliver measurable product and business outcomes.Key ResponsibilitiesDesign, train, and evaluate machine learning models for classification, recommendation, ranking, forecasting, and NLP applicationsBuild reproducible data and feature pipelines using Python, SQL, Spark, or equivalent distributed processing toolsDeploy and serve models through AWS SageMaker, Vertex AI, Kubernetes, or comparable cloud platforms with clear versioning and rollback processesDevelop model APIs and batch inference workflows that meet defined requirements for throughput, latency, scalability, and reliabilityImplement monitoring for data quality, feature drift, model performance, service health, and operational regressionsCollaborate with data scientists and software engineers to productionize experiments, improve evaluation methodology, and resolve model performance issuesWrite tested, maintainable code and contribute to technical design reviews, CI/CD workflows, documentation, and ML engineering standardsWhat We Are Looking For3–8 years of experience in machine learning engineering, applied machine learning, or a closely related software engineering role, including production model deploymentStrong Python skills and hands-on experience with PyTorch, TensorFlow, scikit-learn, or comparable ML frameworksSolid understanding of machine learning fundamentals, including feature engineering, model selection, regularization, cross-validation, and evaluation metricsExperience building data pipelines with SQL and tools such as Spark, Airflow, dbt, or equivalent workflow and orchestration technologiesPractical experience with cloud infrastructure and MLOps practices, including Docker, Kubernetes, CI/CD, model registry, experiment tracking, and monitoringBachelor’s or master’s degree in computer science, machine learning, statistics, engineering, or a related technical fieldBonus: Experience with LLMs, embeddings, vector search, real-time inference, feature stores, causal modeling, or distributed model training","company":"Evlo Ai","rawCompany":"evlo ai","city":"Denver","state":"CO","isRemote":false,"isActive":false,"createdAt":"2026-09-16T09:14:16.262Z","occupations":[{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"}],"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":"Machine Learning Engineer","description":"About The RoleThe Machine Learning Engineer owns the full lifecycle of production ML systems, from data preparation and model development through deployment, monitoring, and iteration. The work spans supervised learning, ranking, forecasting, and NLP use cases where accuracy, inference latency, and operational reliability all matter.Based in Denver, CO with a remote work structure, the role partners with data scientists, software engineers, and platform teams to turn research prototypes into dependable services. The team uses Python, PyTorch or scikit-learn, cloud infrastructure, and modern MLOps practices to deliver measurable product and business outcomes.Key ResponsibilitiesDesign, train, and evaluate machine learning models for classification, recommendation, ranking, forecasting, and NLP applicationsBuild reproducible data and feature pipelines using Python, SQL, Spark, or equivalent distributed processing toolsDeploy and serve models through AWS SageMaker, Vertex AI, Kubernetes, or comparable cloud platforms with clear versioning and rollback processesDevelop model APIs and batch inference workflows that meet defined requirements for throughput, latency, scalability, and reliabilityImplement monitoring for data quality, feature drift, model performance, service health, and operational regressionsCollaborate with data scientists and software engineers to productionize experiments, improve evaluation methodology, and resolve model performance issuesWrite tested, maintainable code and contribute to technical design reviews, CI/CD workflows, documentation, and ML engineering standardsWhat We Are Looking For3–8 years of experience in machine learning engineering, applied machine learning, or a closely related software engineering role, including production model deploymentStrong Python skills and hands-on experience with PyTorch, TensorFlow, scikit-learn, or comparable ML frameworksSolid understanding of machine learning fundamentals, including feature engineering, model selection, regularization, cross-validation, and evaluation metricsExperience building data pipelines with SQL and tools such as Spark, Airflow, dbt, or equivalent workflow and orchestration technologiesPractical experience with cloud infrastructure and MLOps practices, including Docker, Kubernetes, CI/CD, model registry, experiment tracking, and monitoringBachelor’s or master’s degree in computer science, machine learning, statistics, engineering, or a related technical fieldBonus: Experience with LLMs, embeddings, vector search, real-time inference, feature stores, causal modeling, or distributed model training","datePosted":"2026-09-16T09:14:16.262Z","dateModified":"2026-09-16T09:14:16.262Z","hiringOrganization":{"@type":"Organization","name":"Evlo Ai","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Denver","addressRegion":"CO","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"377850bf60ea8faa12b2df5e"},"url":"https://jobsearcher.com/jobs/377850bf60ea8faa12b2df5e"}}