Job Opportunities API

ABOUT THE ROLE A Series A AI/ML startup focused on model training and evaluation is looking for a Founding ML Engineer to build and scale core machine learning systems from the ground up. This is a hands-on, high-impact role for someone who thrives at the intersection of research intuition and engineering execution. You will work closely with the founding team to design, train, and ship production-grade ML models while helping set the foundation for technical culture, infrastructure, and research practices. WHAT YOU'LL DO - Build and optimize end-to-end ML pipelines, from data ingestion to deployment. - Implement and fine-tune LLMs, embeddings, and generative models for real-world applications. - Develop efficient training and inference systems leveraging distributed compute. - Partner with data and product teams to translate ideas into measurable ML impact. - Contribute to model monitoring, evaluation, and continual learning frameworks. - Establish best practices in model versioning, reproducibility, and scalability. WHAT WE'RE LOOKING FOR - 3–10 years of hands-on experience as an ML Engineer, Applied Scientist, or Research Engineer. - Proficiency in Python and at least one of PyTorch, TensorFlow, or JAX. - Experience building production-grade end-to-end ML pipelines (data ingestion, training, deployment). - Experience implementing and fine-tuning LLMs, embeddings, and generative models for real-world applications. - Hands-on experience with distributed training/inference and scalable ML systems. - Experience with cloud platforms (AWS, GCP, or Azure) and ML tooling (MLflow, Weights & Biases) for experimentation and model tracking. - Strong collaboration skills; ability to work cross-functionally with data and product teams. - Bias for action, autonomy, and eagerness to shape something from scratch. LOCATION This role is on-site in Mountain View, California. Authorization to work in the US without visa sponsorship is required. COMPENSATION $220,000 – $300,000 USD annually, commensurate with experience.