Machine Learning Engineer

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