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 Role You'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 data Building and maintaining ML pipelines from experimentation through to production Working closely with the product and engineering teams to translate model capabilities into user-facing features Contributing to architecture decisions on a team small enough that your opinion genuinely shapes direction Improving model performance, reliability, and inference speed as the customer base scales What 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 JAX Experience with NLP, large language models, or agentic AI systems is a strong plus Comfort working with noisy, domain-specific datasets where feature engineering still matters Startup mentality — you figure things out, you don't wait for perfect specs Based in Austin or willing to relocate — this team works best in person Show more Show less