{"schemaVersion":"jobsearcher.job.v1","id":"ef0c6dd241ba0341c2fda41e","url":"https://jobsearcher.com/jobs/ef0c6dd241ba0341c2fda41e","canonicalUrl":"https://jobsearcher.com/jobs/ef0c6dd241ba0341c2fda41e","title":"Machine Learning Engineer","description":"Machine Learning Engineer — Austin, TX (Hybrid)Compensation: $160,000 – $200,000 base + equity + benefits Stage: Series A | Backed by top-tier institutional investors Location: Austin, TX — hybrid (3 days in-office)We're working with a well-funded Austin AI company that's doing genuinely interesting work at the intersection of machine learning and enterprise software. This isn't an \"add AI to an existing product\" story — ML is the product, and the team building it is small, senior, and moves fast.They've recently closed a significant Series A from investors with strong track records in enterprise and security software. The founding team has deep domain expertise and a clear thesis on where their market is going. They're now growing the ML team to meet demand from enterprise customers who are already live and paying.The RoleYou'll be one of a small number of ML engineers working directly on core model development and deployment. The problems are hard, the data is messy and domain-specific, and the solutions need to work reliably in high-stakes enterprise environments. You'll have real ownership — no abstraction layers between you and the work that matters.What you'll be doing:Designing, training, and evaluating ML models on complex, unstructured real-world dataBuilding and maintaining ML pipelines from experimentation through to productionWorking closely with the product and engineering teams to translate model capabilities into user-facing featuresContributing to architecture decisions on a team small enough that your opinion genuinely shapes directionImproving model performance, reliability, and inference speed as the customer base scalesWhat we're looking for:4+ years of hands-on ML engineering experience (not just ML research — you've shipped models to production)Strong Python fundamentals and experience with PyTorch or JAXExperience with NLP, large language models, or agentic AI systems is a strong plusComfort working with noisy, domain-specific datasets where feature engineering still mattersStartup mentality — you figure things out, you don't wait for perfect specsBased in Austin or willing to relocate — this team works best in person","company":"Platform Recruitment","rawCompany":"platform recruitment","city":"Austin","state":"TX","isRemote":false,"isActive":false,"createdAt":"2026-06-18T10:08:51.316Z","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":"Machine Learning Engineer","description":"Machine Learning Engineer — Austin, TX (Hybrid)Compensation: $160,000 – $200,000 base + equity + benefits Stage: Series A | Backed by top-tier institutional investors Location: Austin, TX — hybrid (3 days in-office)We're working with a well-funded Austin AI company that's doing genuinely interesting work at the intersection of machine learning and enterprise software. This isn't an \"add AI to an existing product\" story — ML is the product, and the team building it is small, senior, and moves fast.They've recently closed a significant Series A from investors with strong track records in enterprise and security software. The founding team has deep domain expertise and a clear thesis on where their market is going. They're now growing the ML team to meet demand from enterprise customers who are already live and paying.The RoleYou'll be one of a small number of ML engineers working directly on core model development and deployment. The problems are hard, the data is messy and domain-specific, and the solutions need to work reliably in high-stakes enterprise environments. You'll have real ownership — no abstraction layers between you and the work that matters.What you'll be doing:Designing, training, and evaluating ML models on complex, unstructured real-world dataBuilding and maintaining ML pipelines from experimentation through to productionWorking closely with the product and engineering teams to translate model capabilities into user-facing featuresContributing to architecture decisions on a team small enough that your opinion genuinely shapes directionImproving model performance, reliability, and inference speed as the customer base scalesWhat we're looking for:4+ years of hands-on ML engineering experience (not just ML research — you've shipped models to production)Strong Python fundamentals and experience with PyTorch or JAXExperience with NLP, large language models, or agentic AI systems is a strong plusComfort working with noisy, domain-specific datasets where feature engineering still mattersStartup mentality — you figure things out, you don't wait for perfect specsBased in Austin or willing to relocate — this team works best in person","datePosted":"2026-06-18T10:08:51.316Z","dateModified":"2026-06-18T10:08:51.316Z","hiringOrganization":{"@type":"Organization","name":"Platform Recruitment","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Austin","addressRegion":"TX","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"ef0c6dd241ba0341c2fda41e"},"url":"https://jobsearcher.com/jobs/ef0c6dd241ba0341c2fda41e"}}