{"schemaVersion":"jobsearcher.job.v1","id":"62b6f83150be02a5537d078f","url":"https://jobsearcher.com/jobs/62b6f83150be02a5537d078f","canonicalUrl":"https://jobsearcher.com/jobs/62b6f83150be02a5537d078f","title":"Senior Machine Learning Engineer","description":"We're partnering with a fast-growing technology company that's building machine learning systems at significant scale to solve complex real-world challenges. Their platform processes billions of transactions annually and uses advanced AI to power intelligent decision-making for millions of end users.The Role Partner with product managers and engineers to translate business problems into scalable machine learning solutions. Design, develop and deploy production-ready machine learning models across areas such as ranking, prediction, optimisation, forecasting and recommendation. Build robust data pipelines, engineer high-quality features and integrate models into scalable production infrastructure. Monitor model performance, detect drift and continuously improve model accuracy through retraining and experimentation. Write clean, well-tested, production-quality code and contribute to engineering best practices across testing, reliability and performance. Research emerging machine learning techniques, prototype new approaches and validate ideas through offline and online experimentation.What You'll Need PhD or Master's degree in Computer Science, Statistics, Mathematics or a related quantitative discipline (or equivalent industry experience). Strong background in machine learning and software engineering with experience delivering production ML systems. Expertise in recommender systems, Bayesian machine learning, multi-task learning, meta-learning, ranking, prediction or optimisation models. At least 3 years of experience building end-to-end machine learning systems, including training, deployment, serving and monitoring. Experience with modern ML infrastructure such as TensorFlow, Kubeflow (or similar) and feature stores is highly desirable. Familiarity with large-scale deep learning architectures used for recommendation or ranking systems is a plus.What's On Offer Highly competitive salary ($335k-$400k total compensation, $210k-$260k base) Equity package included Comprehensive benefits Opportunity to join a highly technical engineering team where machine learning sits at the core of the product.Apply via Haystack today!","company":"Haystack","rawCompany":"haystack","city":"Austin","state":"TX","isRemote":false,"isActive":false,"createdAt":"2026-08-01T09:17:25.064Z","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":"513210","title":"Software Publishers","slug":"software-publishers"},{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Senior Machine Learning Engineer","description":"We're partnering with a fast-growing technology company that's building machine learning systems at significant scale to solve complex real-world challenges. Their platform processes billions of transactions annually and uses advanced AI to power intelligent decision-making for millions of end users.The Role Partner with product managers and engineers to translate business problems into scalable machine learning solutions. Design, develop and deploy production-ready machine learning models across areas such as ranking, prediction, optimisation, forecasting and recommendation. Build robust data pipelines, engineer high-quality features and integrate models into scalable production infrastructure. Monitor model performance, detect drift and continuously improve model accuracy through retraining and experimentation. Write clean, well-tested, production-quality code and contribute to engineering best practices across testing, reliability and performance. Research emerging machine learning techniques, prototype new approaches and validate ideas through offline and online experimentation.What You'll Need PhD or Master's degree in Computer Science, Statistics, Mathematics or a related quantitative discipline (or equivalent industry experience). Strong background in machine learning and software engineering with experience delivering production ML systems. Expertise in recommender systems, Bayesian machine learning, multi-task learning, meta-learning, ranking, prediction or optimisation models. At least 3 years of experience building end-to-end machine learning systems, including training, deployment, serving and monitoring. Experience with modern ML infrastructure such as TensorFlow, Kubeflow (or similar) and feature stores is highly desirable. Familiarity with large-scale deep learning architectures used for recommendation or ranking systems is a plus.What's On Offer Highly competitive salary ($335k-$400k total compensation, $210k-$260k base) Equity package included Comprehensive benefits Opportunity to join a highly technical engineering team where machine learning sits at the core of the product.Apply via Haystack today!","datePosted":"2026-08-01T09:17:25.064Z","dateModified":"2026-08-01T09:17:25.064Z","hiringOrganization":{"@type":"Organization","name":"Haystack","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Austin","addressRegion":"TX","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"62b6f83150be02a5537d078f"},"url":"https://jobsearcher.com/jobs/62b6f83150be02a5537d078f"}}