Talener
- 5+ years of professional experience, including some experience working with large amounts of data, including text, images and videos. This is a must have.
- Should have experience working for either a media firm or a large, real-time environment where uptime is paramount.
- Hands-on production experience deploying and operating ML inference systems
- Strong AWS SageMaker experience – pipelines, endpoints, monitoring, multi-environment deployments
- Python – core to day-to-day work across pipelines and tooling
- PyTorch and TensorFlow from an ops/serving perspective (not modeling)
- BERT/transformer-based NLP models in a production context
- CI/CD pipeline experience – Jenkins and/or GitLab
- Containerized inference and autoscaling – model deployment and orchestration
- GPU/CPU compute selection, benchmarking, and optimization for production ML workloads
- Monitoring, alerting, drift detection, and A/B testing frameworks for ML in production
- Comfortable in a shared ownership model across ML, Data Science, DevOps, and Platform teams
- Computer vision or ranking/reranking systems experience
- Familiarity with ANN methods (HNSW, etc.)
- Experience running ML workloads over large-scale media datasets (text, image, video)
{“@context”:”http://schema.org”,”@type”:”JobPosting”,”baseSalary”:null,”datePosted”:”2026-05-22″,”validThrough”:”2027-05-22″,”description”:”<div fr-original-style="" style="box-sizing: border-box; font-family: inherit; font-size: inherit;"><strong fr-original-style="" style="box-sizing: border-box; font-weight: bold; font-family: inherit; font-size: inherit;"><span fr-original-style="font-family: Tahoma, Geneva, sans-serif; font-size: 14px;" style="font-family: Tahoma, Geneva, sans-serif; font-size: 14px; box-sizing: border-box;">Title:</span></strong><span fr-original-style="font-size: 14px;" style="font-size: 14px; box-sizing: border-box;"><span fr-original-style="font-family: Tahoma,Geneva,sans-serif;" style="font-family: Tahoma, Geneva, sans-serif; box-sizing: border-box;"> MLOps Engineer</span></span></div><div fr-original-style="" style="box-sizing: border-box; font-family: inherit; font-size: inherit;"><span fr-original-style="font-size: 14px;" style="font-size: 14px; box-sizing: border-box;"><span fr-original-style="font-family: Tahoma,Geneva,sans-serif;" style="font-family: Tahoma, Geneva, sans-serif; box-sizing: border-box;"><br style="font-family: inherit; font-size: inherit; box-sizing: border-box;" fr-original-style="font-family: inherit; font-size: inherit; box-sizing: border-box;"></span></span></div><div fr-original-style="" style="box-sizing: border-box; font-family: inherit; font-size: inherit;"><span fr-original-style="font-size: 14px;" style="font-size: 14px; box-sizing: border-box;"><span fr-original-style="font-family: Tahoma,Geneva,sans-serif;" style="font-family: Tahoma, Geneva, sans-serif; box-sizing: border-box;"><strong fr-original-style="" style="box-sizing: border-box; font-weight: bold; font-family: inherit; font-size: inherit;">Location:</strong> Remote</span></span></div><div fr-original-style="" style="box-sizing: border-box; font-family: inherit; font-size: inherit;"><span fr-original-style="font-size: 14px;" style="font-size: 14px; box-sizing: border-box;"><span fr-original-style="font-family: Tahoma,Geneva,sans-serif;" style="font-family: Tahoma, Geneva, sans-serif; box-sizing: border-box;"><br style="font-family: inherit; font-size: inherit; box-sizing: border-box;" fr-original-style="font-family: inherit; font-size: inherit; box-sizing: border-box;"></span></span></div><div fr-original-style="" style="box-sizing: border-box; font-family: inherit; font-size: inherit;"><span fr-original-style="font-size: 14px;" style="font-size: 14px; box-sizing: border-box;"><span fr-original-style="font-family: Tahoma,Geneva,sans-serif;" style="font-family: Tahoma, Geneva, sans-serif; box-sizing: border-box;"><strong fr-original-style="" style="box-sizing: border-box; font-weight: bold; font-family: inherit; font-size: inherit;">Client: </strong>Global newswire and media organization. Their content reaches more than half the global population daily. The tech org is modern and investing heavily in ML infrastructure to support large-scale media processing across text, image, and video.</span></span></div><div fr-original-style="" style="box-sizing: border-box; font-family: inherit; font-size: inherit;"><span fr-original-style="font-size: 14px;" style="font-size: 14px; box-sizing: border-box;"><span fr-original-style="font-family: Tahoma,Geneva,sans-serif;" style="font-family: Tahoma, Geneva, sans-serif; box-sizing: border-box;"><br style="font-family: inherit; font-size: inherit; box-sizing: border-box;" fr-original-style="font-family: inherit; font-size: inherit; box-sizing: border-box;"></span></span></div><div fr-original-style="" style="box-sizing: border-box; font-family: inherit; font-size: inherit;"><span fr-original-style="font-size: 14px;" style="font-size: 14px; box-sizing: border-box;"><span fr-original-style="font-family: Tahoma,Geneva,sans-serif;" style="font-family: Tahoma, Geneva, sans-serif; box-sizing: border-box;"><strong fr-original-style="" style="box-sizing: border-box; font-weight: bold; font-family: inherit; font-size: inherit;">Role Description</strong></span></span></div><div fr-original-style="" style="box-sizing: border-box; font-family: inherit; font-size: inherit;"><span fr-original-style="font-size: 14px;" style="font-size: 14px; box-sizing: border-box;"><span fr-original-style="font-family: Tahoma,Geneva,sans-serif;" style="font-family: Tahoma, Geneva, sans-serif; box-sizing: border-box;">This is a production operations role – not a data science or modeling role. You'd be owning the full lifecycle of ML systems in production: deploying, scaling, monitoring, and governing inference pipelines so they run reliably, cost-effectively, and at scale.</span></span></div><div fr-original-style="" style="box-sizing: border-box; font-family: inherit; font-size: inherit;"><span fr-original-style="font-size: 14px;" style="font-size: 14px; box-sizing: border-box;"><span fr-original-style="font-family: Tahoma,Geneva,sans-serif;" style="font-family: Tahoma, Geneva, sans-serif; box-sizing: border-box;">You're the person who makes sure what ML Engineers and Data Scientists build actually works in the real world – safely promoted across Dev, QA, and Prod, hitting SLAs, and not creating infrastructure headaches. The team runs hundreds of thousands of queries per day across text, image, and video pipelines – production stability and cost control are non-negotiable.</span></span></div><div fr-original-style="" style="box-sizing: border-box; font-family: inherit; font-size: inherit;"><span fr-original-style="font-size: 14px;" style="font-size: 14px; box-sizing: border-box;"><span fr-original-style="font-family: Tahoma,Geneva,sans-serif;" style="font-family: Tahoma, Geneva, sans-serif; box-sizing: border-box;">You'll also be building the standard – establishing deployment patterns, containerization strategies, environment isolation, versioned rollouts, rollback mechanisms, and monitoring frameworks the org will run on going forward.</span></span></div><div fr-original-style="" style="box-sizing: border-box; font-family: inherit; font-size: inherit;"><span fr-original-style="font-size: 14px;" style="font-size: 14px; box-sizing: border-box;"><span fr-original-style="font-family: Tahoma,Geneva,sans-serif;" style="font-family: Tahoma, Geneva, sans-serif; box-sizing: border-box;">Clear scope: you own deployment, infrastructure, monitoring, reliability, and cost governance. Model architecture and data science outputs stay with the ML and Data Science teams.</span></span></div><div fr-original-style="" style="box-sizing: border-box; font-family: inherit; font-size: inherit;"><span fr-original-style="font-size: 14px;" style="font-size: 14px; box-sizing: border-box;"><span fr-original-style="font-family: Tahoma,Geneva,sans-serif;" style="font-family: Tahoma, Geneva, sans-serif; box-sizing: border-box;"><strong fr-original-style="" style="box-sizing: border-box; font-weight: bold; font-family: inherit; font-size: inherit;"><br style="font-family: inherit; font-size: inherit; box-sizing: border-box;" fr-original-style="font-family: inherit; font-size: inherit; box-sizing: border-box;"></strong></span></span></div><div fr-original-style="" style="box-sizing: border-box; font-family: inherit; font-size: inherit;"><span fr-original-style="font-size: 14px;" style="font-size: 14px; box-sizing: border-box;"><span fr-original-style="font-family: Tahoma,Geneva,sans-serif;" style="font-family: Tahoma, Geneva, sans-serif; box-sizing: border-box;"><strong fr-original-style="" style="box-sizing: border-box; font-weight: bold; font-family: inherit; font-size: inherit;">Required Skills</strong></span></span></div><ul fr-original-style="font-family: inherit; font-size: inherit; box-sizing: border-box; margin-top: 0px; margin-bottom: 10px; color: rgb(74, 74, 74); font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-indent: 0px; text-transform: none; widows: 2; word-spacing: 0px; -webkit-text-stroke-width: 0px; white-space: normal; background-color: rgb(255, 255, 255); text-decoration-thickness: initial; text-decoration-style: initial; text-decoration-color: initial;" style="font-family: inherit; font-size: inherit; box-sizing: border-box; margin-top: 0px; margin-bottom: 10px; color: rgb(74, 74, 74); font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-indent: 0px; text-transform: none; widows: 2; word-spacing: 0px; -webkit-text-stroke-width: 0px; white-space: normal; background-color: rgb(255, 255, 255); text-decoration-thickness: initial; text-decoration-style: initial; text-decoration-color: initial;"><li fr-original-style="font-family: Tahoma, Geneva, sans-serif; font-size: 14px; box-sizing: border-box;" style="font-family: Tahoma, Geneva, sans-serif; font-size: 14px; box-sizing: border-box;">5+ years of professional experience, including some experience working with large amounts of data, including text, images and videos. This is a must have. </li><li fr-original-style="font-family: Tahoma, Geneva, sans-serif; font-size: 14px; box-sizing: border-box;" style="font-family: Tahoma, Geneva, sans-serif; font-size: 14px; box-sizing: border-box;">Should have experience working for either a media firm or a large, real-time environment where uptime is paramount. </li><li fr-original-style="font-family: Tahoma, Geneva, sans-serif; font-size: 14px; box-sizing: border-box;" style="font-family: Tahoma, Geneva, sans-serif; font-size: 14px; box-sizing: border-box;">Hands-on production experience deploying and operating ML inference systems</li><li fr-original-style="font-family: Tahoma, Geneva, sans-serif; font-size: 14px; box-sizing: border-box;" style="font-family: Tahoma, Geneva, sans-serif; font-size: 14px; box-sizing: border-box;">Strong AWS SageMaker experience – pipelines, endpoints, monitoring, multi-environment deployments</li><li fr-original-style="font-family: Tahoma, Geneva, sans-serif; font-size: 14px; box-sizing: border-box;" style="font-family: Tahoma, Geneva, sans-serif; font-size: 14px; box-sizing: border-box;">Python – core to day-to-day work across pipelines and tooling</li><li fr-original-style="font-family: Tahoma, Geneva, sans-serif; font-size: 14px; box-sizing: border-box;" style="font-family: Tahoma, Geneva, sans-serif; font-size: 14px; box-sizing: border-box;">PyTorch and TensorFlow from an ops/serving perspective (not modeling)</li><li fr-original-style="font-family: Tahoma, Geneva, sans-serif; font-size: 14px; box-sizing: border-box;" style="font-family: Tahoma, Geneva, sans-serif; font-size: 14px; box-sizing: border-box;">BERT/transformer-based NLP models in a production context</li><li fr-original-style="font-family: Tahoma, Geneva, sans-serif; font-size: 14px; box-sizing: border-box;" style="font-family: Tahoma, Geneva, sans-serif; font-size: 14px; box-sizing: border-box;">CI/CD pipeline experience – Jenkins and/or GitLab</li><li fr-original-style="font-family: Tahoma, Geneva, sans-serif; font-size: 14px; box-sizing: border-box;" style="font-family: Tahoma, Geneva, sans-serif; font-size: 14px; box-sizing: border-box;">Containerized inference and autoscaling – model deployment and orchestration</li><li fr-original-style="font-family: Tahoma, Geneva, sans-serif; font-size: 14px; box-sizing: border-box;" style="font-family: Tahoma, Geneva, sans-serif; font-size: 14px; box-sizing: border-box;">GPU/CPU compute selection, benchmarking, and optimization for production ML workloads</li><li fr-original-style="font-family: Tahoma, Geneva, sans-serif; font-size: 14px; box-sizing: border-box;" style="font-family: Tahoma, Geneva, sans-serif; font-size: 14px; box-sizing: border-box;">Monitoring, alerting, drift detection, and A/B testing frameworks for ML in production</li><li fr-original-style="font-family: Tahoma, Geneva, sans-serif; font-size: 14px; box-sizing: border-box;" style="font-family: Tahoma, Geneva, sans-serif; font-size: 14px; box-sizing: border-box;">Comfortable in a shared ownership model across ML, Data Science, DevOps, and Platform teams</li></ul><div fr-original-style="" style="box-sizing: border-box; font-family: inherit; font-size: inherit;"><span fr-original-style="font-size: 14px;" style="font-size: 14px; box-sizing: border-box;"><span fr-original-style="font-family: Tahoma,Geneva,sans-serif;" style="font-family: Tahoma, Geneva, sans-serif; box-sizing: border-box;"><strong fr-original-style="" style="box-sizing: border-box; font-weight: bold; font-family: inherit; font-size: inherit;">Nice to Have</strong></span></span></div><ul fr-original-style="font-family: inherit; font-size: inherit; box-sizing: border-box; margin-top: 0px; margin-bottom: 10px; color: rgb(74, 74, 74); font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-indent: 0px; text-transform: none; widows: 2; word-spacing: 0px; -webkit-text-stroke-width: 0px; white-space: normal; background-color: rgb(255, 255, 255); text-decoration-thickness: initial; text-decoration-style: initial; text-decoration-color: initial;" style="font-family: inherit; font-size: inherit; box-sizing: border-box; margin-top: 0px; margin-bottom: 10px; color: rgb(74, 74, 74); font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-indent: 0px; text-transform: none; widows: 2; word-spacing: 0px; -webkit-text-stroke-width: 0px; white-space: normal; background-color: rgb(255, 255, 255); text-decoration-thickness: initial; text-decoration-style: initial; text-decoration-color: initial;"><li fr-original-style="font-family: Tahoma, Geneva, sans-serif; font-size: 14px; box-sizing: border-box;" style="font-family: Tahoma, Geneva, sans-serif; font-size: 14px; box-sizing: border-box;">Computer vision or ranking/reranking systems experience</li><li fr-original-style="font-family: Tahoma, Geneva, sans-serif; font-size: 14px; box-sizing: border-box;" style="font-family: Tahoma, Geneva, sans-serif; font-size: 14px; box-sizing: border-box;">Familiarity with ANN methods (HNSW, etc.)</li><li fr-original-style="font-family: Tahoma, Geneva, sans-serif; font-size: 14px; box-sizing: border-box;" style="font-family: Tahoma, Geneva, sans-serif; font-size: 14px; box-sizing: border-box;">Experience running ML workloads over large-scale media datasets (text, image, video)</li></ul><div fr-original-style="" style="box-sizing: border-box; font-family: inherit; font-size: inherit;"><span fr-original-style="font-size: 14px;" style="font-size: 14px; box-sizing: border-box;"><span fr-original-style="font-family: Tahoma,Geneva,sans-serif;" style="font-family: Tahoma, Geneva, sans-serif; box-sizing: border-box;"><strong fr-original-style="" style="box-sizing: border-box; font-weight: bold; font-family: inherit; font-size: inherit;">Compensation</strong></span></span></div><div fr-original-style="" style="box-sizing: border-box; font-family: inherit; font-size: inherit;"><span fr-original-style="font-size: 14px;" style="font-size: 14px; box-sizing: border-box;"><span fr-original-style="font-family: Tahoma,Geneva,sans-serif;" style="font-family: Tahoma, Geneva, sans-serif; box-sizing: border-box;">Base salary up to $140,000.00 + 10% bonus target</span></span></div><div fr-original-style="" style="box-sizing: border-box; font-family: inherit; font-size: inherit;"><span fr-original-style="font-size: 14px;" style="font-size: 14px; box-sizing: border-box;"><span fr-original-style="font-family: Tahoma,Geneva,sans-serif;" style="font-family: Tahoma, Geneva, sans-serif; box-sizing: border-box;"><br style="font-family: inherit; font-size: inherit; box-sizing: border-box;" fr-original-style="font-family: inherit; font-size: inherit; box-sizing: border-box;"></span></span></div><div fr-original-style="" style="box-sizing: border-box; font-family: inherit; font-size: inherit;"><span fr-original-style="font-size: 14px;" style="font-size: 14px; box-sizing: border-box;"><span fr-original-style="font-family: Tahoma,Geneva,sans-serif;" style="font-family: Tahoma, Geneva, sans-serif; box-sizing: border-box;">For additional information or to apply, please contact Bethany Moulthrop at <a fr-original-style="" href="mailto:bmoulthrop@gmail.com" style="box-sizing: border-box; user-select: auto; background: transparent; color: rgb(0, 112, 192); text-decoration: none; font-family: inherit; font-size: inherit; cursor: pointer;">bmoulthrop@gmail.com</a>.</span></span></div><div fr-original-style="" style="box-sizing: border-box; font-family: inherit; font-size: inherit;"><span fr-original-style="font-size: 14px;" style="font-size: 14px; box-sizing: border-box;"><span fr-original-style="font-family: Tahoma,Geneva,sans-serif;" style="font-family: Tahoma, Geneva, sans-serif; box-sizing: border-box;"><br fr-original-style=""></span></span></div><div fr-original-style="" style="box-sizing: border-box; font-family: inherit; font-size: inherit;"><span fr-original-style="font-family: Tahoma, Geneva, sans-serif; font-size: 14px;" style="font-family: Tahoma, Geneva, sans-serif; font-size: 14px; box-sizing: border-box;">#LI-REMOTE</span></div>”,”employmentType”:”FULL_TIME”,”hiringOrganization”:{“@type”:”Organization”,”name”:”Talener”},”jobLocation”:{“@type”:”Place”,”address”:{“@type”:”PostalAddress”,”streetAddress”:null,”addressLocality”:”Greater New York City Area”,”addressRegion”:”NY”,”postalCode”:null,”addressCountry”:null}},”title”:”MLOps Engineer”,”url”:”https://talener.com/jobs/?cjobid=BA759319522&rpid=1630131&postid=3FEJX7FGpMA”,”identifier”:{“@type”:”PropertyValue”,”name”:”Talener”,”value”:null}}