Founding Engineer – ML Research

### About the Role A well-funded Series A AI/ML platform company is looking for a **Founding Engineer — ML Research** to build and scale its research backbone. You'll bridge applied machine learning and systems engineering, turning cutting-edge ideas into reliable, production-ready models. As an early team member, you'll have direct impact on model performance, data quality, and the company's core technical foundations in generative and multimodal AI. ### What You'll Do - Design, train, and evaluate ML models — including LLMs, diffusion models, and domain-specific architectures. - Develop scalable experimentation pipelines spanning data ingestion, model training, and evaluation workflows. - Collaborate with data and infrastructure teams to optimize training throughput and model quality. - Contribute to open research, internal benchmarks, and new techniques in multimodal and generative AI. - Rapidly prototype research ideas and productionize them into usable models and tools. - Define and promote standards for research rigor, documentation, and reproducibility across the engineering org. ### What We're Looking For - **3–10 years** of experience in ML research, applied ML, or ML systems engineering. - Deep familiarity with **PyTorch, JAX, or TensorFlow** and hands-on experience with architectures such as Transformers, Diffusion models, or RLHF. - Strong foundations in data processing, distributed training, and evaluation metrics. - Demonstrated ability to move from research papers to working prototypes to production-ready code. - Curiosity about emerging ML paradigms — multimodality, self-learning, synthetic data, and agentic systems. - Passion for building from zero to one in a high-velocity startup environment. - **Nice to have:** Open research contributions, published benchmarks, or peer-reviewed publications in relevant ML research areas. ### Compensation & Benefits - **Salary:** $220,000 – $300,000 USD annually - Equity participation as a founding team member - **Visa sponsorship:** Not available — candidates must be authorized to work in the US ### Location This is an **on-site role** based in the **San Francisco Bay Area / Mountain View, California**. Remote arrangements are not available for this position.