Machine Learning Research Scientist

Company Description At Autoscience Institute, we create AI systems that autonomously conduct AI research. Recently, we announced the first AI agent to autonomously create peer-reviewed literature (ICLR 2025 Workshops). We are passionate about pushing the boundaries of artificial intelligence and contributing to groundbreaking advancements in the field. Role Description This is a full-time on-site role for a Machine Learning Research Scientist located in the San Francisco Bay Area. - Work directly with the founder to develop autonomous research systems that ideate, experiment, and improve customer models. - Collaborate with the engineering team to build and deploy production-ready research systems. - RL post-train and fine-tune reasoning models to automate components of the machine learning research process. - Stay current with the latest developments in AI research and automation. Qualifications: - Education: PhD or equivalent research experience in Computer Science, Machine Learning, Artificial Intelligence, or a related field. Exceptional candidates with strong research contributions are encouraged to apply regardless of formal degree. - Research: Publishing in top-tier AI/ML conferences (e.g., NeurIPS, ICML, ICLR, etc) or equivalent industry experience at corporate AI research labs (Microsoft, Google, Nvidia, TRI etc). - Technical: Expertise in training machine learning models, including deep learning, reinforcement learning or genetic algorithms. This does not include building multi-agent systems using LLM APIs or building RAG-based agents. - Curiosity: Passion for accelerating scientific discovery through AI and willingness to explore uncharted directions with minimal supervision. Recommended Qualifications - Systems: Experience building scalable and production-ready machine learning pipelines or large-scale model training (distributed model training over >64 GPUs). - Science: Any background or proven interested in Automated Scientific Research is a plus. Benef