{"schemaVersion":"jobsearcher.job.v1","id":"1a34b1fd00e1f4a88551fee1","url":"https://jobsearcher.com/jobs/1a34b1fd00e1f4a88551fee1","canonicalUrl":"https://jobsearcher.com/jobs/1a34b1fd00e1f4a88551fee1","title":"MLOps Engineer / DevOps Engineer","description":"MLOps Engineer / DevOps Engineer\n\n*Candidates must be legally authorized to work in the United States on a permanent and ongoing basis without the need for current or future employer-sponsored visa support, including H-1B, OPT, STEM OPT, or any other work authorization requiring sponsorship. Applications from candidates requiring sponsorship now or in the future will not be considered.\n\nIn 2020, we launched CHEF iQ, an ecosystem of connected kitchen appliances designed to transform how people cook and connect through food. Our mission is to make great cooking effortless through intelligent technology, guided experiences, and seamless integration between hardware, software, and AI. As CHEF iQ continues to expand its AI capabilities, we are building the infrastructure and platforms that will power the next generation of connected cooking experiences. From machine learning and computer vision to Generative AI applications, our success depends on scalable, reliable systems that enable rapid innovation and deployment.\n\nWe are seeking a highly detail-oriented MLOps / DevOps Engineer to serve as a critical partner to our Machine Learning Engineer, building and maintaining the cloud infrastructure, deployment pipelines, automation frameworks, and operational foundations that support AI development at scale. This individual will play a key role in improving engineering efficiency, increasing system reliability, and ensuring our AI-powered products can be developed, deployed, and scaled successfully.\n\nThe ideal candidate is passionate about automation, process improvement, and building highly scalable systems. They enjoy creating order from complexity, eliminating operational bottlenecks, and enabling teams to move faster. Experience supporting AI, machine learning, and Generative AI applications in production environments is required.\n\nRole and Responsibilities\nDesign, implement, and maintain scalable AWS cloud infrastructure supporting software, AI, and machine learning applications.\nCreate and manage MLOps infrastructure for model training, deployment, monitoring, versioning, and lifecycle management.\nPartner closely with the Machine Learning Engineer to establish the tools, workflows, and infrastructure required for successful AI development and deployment.\nSupport Generative AI initiatives by building infrastructure and deployment frameworks for applications utilizing AWS Bedrock, foundation models, LLMs, and related AI services.\nBuild and manage Infrastructure as Code (IaC) using Terraform to ensure repeatable, secure, and scalable environments.\nImplement monitoring, logging, observability, and alerting systems across software, infrastructure, and machine learning platforms.\nContinuously identify opportunities to improve engineering processes, reduce manual effort, increase automation, and improve system reliability.\nDevelop and maintain CI/CD pipelines that enable rapid, reliable software and machine learning deployments.\nOptimize cloud environments for scalability, performance, availability, and cost efficiency.\nSupport security, compliance, backup, disaster recovery, and operational best practices across all environments.\nTroubleshoot infrastructure, deployment, and application issues across development, testing, and production environments.\nDocument infrastructure architecture, deployment processes, operational procedures, and engineering standards.\nContribute to establishing best practices for DevOps, MLOps, cloud architecture, and AI operations.\n\nQualifications\n\nPlease Note: Chefman is unable to provide visa sponsorship for this position. Candidates must be legally authorized to work in the United States on a permanent and ongoing basis without the need for current or future employer-sponsored visa support, including H-1B, OPT, STEM OPT, or any other work authorization requiring sponsorship. Applications from candidates requiring sponsorship now or in the future will not be considered.\n\n5+ years of experience in MLOps, DevOps, Site Reliability Engineering (SRE), Platform Engineering, or related software engineering roles.\nStrong hands-on experience with AWS services and cloud-native architecture.\nExperience building and supporting AI and machine learning platforms in AWS environments.\nExperience supporting AI, machine learning, and Generative AI applications in production environments.\nExperience working with AWS Bedrock, Generative AI services, foundation models, LLM-powered applications, or related AI infrastructure.\nStrong experience implementing Infrastructure as Code using Terraform.\nExperience with containerization and orchestration technologies such as Docker and Kubernetes.\nStrong experience building and maintaining CI/CD pipelines and deployment automation.\nExperience supporting machine learning workflows, model deployment, monitoring, and MLOps platforms.\nStrong programming and scripting skills in Python, Bash, or similar languages.\nExperience with monitoring, logging, observability, and operational tooling.\nStrong troubleshooting, systems-thinking, and problem-solving abilities.\nExcellent communication and cross-functional collaboration skills.\nProven track record of improving engineering processes, increasing operational efficiency, and scaling software platforms.\nHighly organized and detail-oriented with a passion for automation and continuous improvement.\n\nPreferred Qualifications\nExperience with vector databases, retrieval-augmented generation (RAG), model serving, and AI infrastructure.\nExperience supporting connected devices, IoT platforms, embedded systems, or consumer technology products.\nDomain expertise in machine learning infrastructure, AI platforms, consumer applications, connected products, or similar technology environments.\nExperience working in fast-paced startup or high-growth product organizations.","company":"Chefman","rawCompany":"chefman","city":"Mahwah","state":"NJ","isRemote":false,"isActive":false,"createdAt":"2026-08-22T14:03:46.406Z","occupations":[{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1244.00","title":"Network and Computer Systems Administrators","slug":"network-and-computer-systems-administrators"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"MLOps Engineer / DevOps Engineer","description":"MLOps Engineer / DevOps Engineer\n\n*Candidates must be legally authorized to work in the United States on a permanent and ongoing basis without the need for current or future employer-sponsored visa support, including H-1B, OPT, STEM OPT, or any other work authorization requiring sponsorship. Applications from candidates requiring sponsorship now or in the future will not be considered.\n\nIn 2020, we launched CHEF iQ, an ecosystem of connected kitchen appliances designed to transform how people cook and connect through food. Our mission is to make great cooking effortless through intelligent technology, guided experiences, and seamless integration between hardware, software, and AI. As CHEF iQ continues to expand its AI capabilities, we are building the infrastructure and platforms that will power the next generation of connected cooking experiences. From machine learning and computer vision to Generative AI applications, our success depends on scalable, reliable systems that enable rapid innovation and deployment.\n\nWe are seeking a highly detail-oriented MLOps / DevOps Engineer to serve as a critical partner to our Machine Learning Engineer, building and maintaining the cloud infrastructure, deployment pipelines, automation frameworks, and operational foundations that support AI development at scale. This individual will play a key role in improving engineering efficiency, increasing system reliability, and ensuring our AI-powered products can be developed, deployed, and scaled successfully.\n\nThe ideal candidate is passionate about automation, process improvement, and building highly scalable systems. They enjoy creating order from complexity, eliminating operational bottlenecks, and enabling teams to move faster. Experience supporting AI, machine learning, and Generative AI applications in production environments is required.\n\nRole and Responsibilities\nDesign, implement, and maintain scalable AWS cloud infrastructure supporting software, AI, and machine learning applications.\nCreate and manage MLOps infrastructure for model training, deployment, monitoring, versioning, and lifecycle management.\nPartner closely with the Machine Learning Engineer to establish the tools, workflows, and infrastructure required for successful AI development and deployment.\nSupport Generative AI initiatives by building infrastructure and deployment frameworks for applications utilizing AWS Bedrock, foundation models, LLMs, and related AI services.\nBuild and manage Infrastructure as Code (IaC) using Terraform to ensure repeatable, secure, and scalable environments.\nImplement monitoring, logging, observability, and alerting systems across software, infrastructure, and machine learning platforms.\nContinuously identify opportunities to improve engineering processes, reduce manual effort, increase automation, and improve system reliability.\nDevelop and maintain CI/CD pipelines that enable rapid, reliable software and machine learning deployments.\nOptimize cloud environments for scalability, performance, availability, and cost efficiency.\nSupport security, compliance, backup, disaster recovery, and operational best practices across all environments.\nTroubleshoot infrastructure, deployment, and application issues across development, testing, and production environments.\nDocument infrastructure architecture, deployment processes, operational procedures, and engineering standards.\nContribute to establishing best practices for DevOps, MLOps, cloud architecture, and AI operations.\n\nQualifications\n\nPlease Note: Chefman is unable to provide visa sponsorship for this position. Candidates must be legally authorized to work in the United States on a permanent and ongoing basis without the need for current or future employer-sponsored visa support, including H-1B, OPT, STEM OPT, or any other work authorization requiring sponsorship. Applications from candidates requiring sponsorship now or in the future will not be considered.\n\n5+ years of experience in MLOps, DevOps, Site Reliability Engineering (SRE), Platform Engineering, or related software engineering roles.\nStrong hands-on experience with AWS services and cloud-native architecture.\nExperience building and supporting AI and machine learning platforms in AWS environments.\nExperience supporting AI, machine learning, and Generative AI applications in production environments.\nExperience working with AWS Bedrock, Generative AI services, foundation models, LLM-powered applications, or related AI infrastructure.\nStrong experience implementing Infrastructure as Code using Terraform.\nExperience with containerization and orchestration technologies such as Docker and Kubernetes.\nStrong experience building and maintaining CI/CD pipelines and deployment automation.\nExperience supporting machine learning workflows, model deployment, monitoring, and MLOps platforms.\nStrong programming and scripting skills in Python, Bash, or similar languages.\nExperience with monitoring, logging, observability, and operational tooling.\nStrong troubleshooting, systems-thinking, and problem-solving abilities.\nExcellent communication and cross-functional collaboration skills.\nProven track record of improving engineering processes, increasing operational efficiency, and scaling software platforms.\nHighly organized and detail-oriented with a passion for automation and continuous improvement.\n\nPreferred Qualifications\nExperience with vector databases, retrieval-augmented generation (RAG), model serving, and AI infrastructure.\nExperience supporting connected devices, IoT platforms, embedded systems, or consumer technology products.\nDomain expertise in machine learning infrastructure, AI platforms, consumer applications, connected products, or similar technology environments.\nExperience working in fast-paced startup or high-growth product organizations.","datePosted":"2026-08-22T14:03:46.406Z","dateModified":"2026-08-22T14:03:46.406Z","hiringOrganization":{"@type":"Organization","name":"Chefman","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Mahwah","addressRegion":"NJ","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"1a34b1fd00e1f4a88551fee1"},"url":"https://jobsearcher.com/jobs/1a34b1fd00e1f4a88551fee1"}}