Research, Post-Training

The Post-Training Researcher at Thinking Machines Lab plays a pivotal role in refining AI models to ensure they are useful, safe, and collaborative for human interaction. This position bridges the gap between raw model intelligence and practical application, blending fundamental research with hands-on engineering. The successful candidate will join a team dedicated to advancing collaborative general intelligence, contributing to a future where AI tools are accessible and tailored to individual needs.

Key responsibilities include developing and iterating on post-training recipes, which encompass datasets, training stages, and hyperparameters, to optimize model performance. The researcher will define and refine evaluation metrics, ensuring they accurately capture the desired outcomes. Additionally, the role involves debugging training configurations, scaling existing methodologies, exploring new training datasets, and publishing research to advance the AI community.

Candidates must possess proficiency in Python and familiarity with at least one deep learning framework such as PyTorch, TensorFlow, or JAX. A bachelor's degree or equivalent experience in Computer Science, Machine Learning, Physics, Mathematics, or a related discipline is required. Strong communication skills are essential, with the ability to articulate complex technical concepts clearly.

The position offers a competitive annual salary ranging from $350,000 to $475,000, depending on experience and qualifications. Benefits include comprehensive health, dental, and vision insurance, unlimited paid time off, paid parental leave, and relocation support as needed.

Thinking Machines Lab fosters a culture of innovation and collaboration, emphasizing the development of AI systems that are customizable and aligned with human values. The company provides growth opportunities through interdisciplinary projects and encourages contributions that move the entire AI community forward.