Company Overview
Arc Institute is a pioneering scientific organization dedicated to curiosity-driven basic research and cutting-edge technology development.
Based in Palo Alto, California, Arc is a non-profit institution founded on the principle that transformative research can thrive under innovative academic models. The institute collaborates closely with Stanford University, UCSF, and UC Berkeley to advance scientific discovery.
At Arc, researchers from diverse disciplines work together to explore the complexities of diseases such as cancer, neurodegeneration, and immune dysfunction, fostering groundbreaking insights and solutions.
About You
- You are a skilled and innovative machine learning engineer with experience in training and evaluating large-scale deep learning models.
- You thrive in a multidisciplinary environment, collaborating closely with computational and experimental biologists at Arc to drive groundbreaking advancements in biological prediction and design.
- You excel at communicating complex technical concepts to researchers outside your domain, making AI-driven insights accessible and impactful.
- You are a lifelong learner, eager to develop and refine models that have transformative effects across multiple biological disciplines.
What You’ll Do
- Optimize and scale cutting-edge foundation models in collaboration with ML researchers and scientists to advance our understanding and design of complex biological systems.
- Develop large-scale distributed training pipelines and efficient inference systems to enhance model performance.
- Establish systematic evaluation frameworks to ensure the robustness and reliability of trained models.
- Stay at the forefront of advancements in large-scale sequence modeling and alignment, integrating the most promising innovations into our research.
- Work closely with experimental biologists to ensure that models address biologically meaningful challenges and evaluations.
- Contribute to the scientific community through journal publications, white papers, and presentations, both internally and externally.
- Build and strengthen collaborations within and beyond Arc Institute, focusing on generative design for biological systems.
- Foster a collaborative, inclusive team culture by sharing expertise and mentoring fellow researchers.
Qualifications
- B.S., M.S., or Ph.D. in Computer Science, Machine Learning, or a related field.
- 5–8+ years of relevant experience in machine learning research or ML engineering in an academic (e.g., Ph.D.) or industry research setting.
- Expertise in machine learning frameworks such as PyTorch or JAX.
- Experience developing distributed training tools such as FSDP, DeepSpeed, or Megatron-LM.
- Strong written and verbal communication skills, with a proven track record of presentations and publications.
- Ability to effectively collaborate with biologists and software/infrastructure engineers.
- Passionate about working in a fast-paced, ambitious, and highly collaborative research environment.