Founding Machine Learning Engineer

<h3>About the Role</h3><p style="min-height:1.5em">This is a founding-level Machine Learning Engineer role at a well-funded Series A AI data and services startup based in Mountain View, CA. You will join a small, high-caliber team building and scaling core ML systems from the ground up — bridging research and engineering to design, train, and ship production-grade models for top AI frontier labs. This is a high-ownership position where your work directly shapes the company's technical culture, infrastructure, and long-term ML impact.</p><p style="min-height:1.5em">The company specializes in high-quality training and post-training data, reinforcement learning environments, and intelligent agents — serving both frontier AI labs and enterprise customers. Visa sponsorship is <strong>not available</strong> for this role.</p><h3>What You'll Do</h3><ul style="min-height:1.5em"><li><p style="min-height:1.5em">Build and optimize end-to-end ML pipelines, from data ingestion through to deployment.</p></li><li><p style="min-height:1.5em">Implement and fine-tune LLMs, embeddings, and generative models for real-world applications.</p></li><li><p style="min-height:1.5em">Develop efficient training and inference systems leveraging distributed compute.</p></li><li><p style="min-height:1.5em">Partner with data and product teams to translate ideas into measurable ML impact.</p></li><li><p style="min-height:1.5em">Contribute to model monitoring, evaluation, and continual learning frameworks.</p></li><li><p style="min-height:1.5em">Establish best practices in model versioning, reproducibility, and scalability.</p></li></ul><h3>What We're Looking For</h3><p style="min-height:1.5em"><strong>Required:</strong></p><ul style="min-height:1.5em"><li><p style="min-height:1.5em">3–10 years of experience as an ML Engineer, Applied Scientist, or Research Engineer.</p></li><li><p style="min-height:1.5em">Proficiency in Python and at least one major ML framework: PyTorch, TensorFlow, or JAX.</p></li><li><p style="min-height:1.5em">Strong grasp of ML fundamentals — data preprocessing, feature engineering, model training, and optimization.</p></li><li><p style="min-height:1.5em">Hands-on experience with distributed systems and cloud ML infrastructure (AWS, GCP, or Azure).</p></li><li><p style="min-height:1.5em">Familiarity with MLOps tooling such as Weights &amp; Biases or MLflow.</p></li><li><p style="min-height:1.5em">Comfort working with large datasets and high-throughput systems.</p></li><li><p style="min-height:1.5em">Strong bias for action, ability to work autonomously, and genuine e...

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