Autonomous ML Research Engineer – Frontier AI

Autoscience; Menlo Park (CA); On-site; USD 180,000 - 230,000; Full time

Benefits offered by this job

Unlimited PTO

Conference attendance support

Competitive compensation against major

Job summary

Autoscience in the San Francisco Bay Area is seeking a Machine Learning Research Engineer for a full-time on-site role. You will work with the founder to develop autonomous research systems that ideate, experiment, and improve customer models, and collaborate with the engineering team to deploy production-ready systems.

Qualifying candidates have Harvard-level CS/ECE/Math excellence and a track record in AI/ML research, with publications in top conferences; strong training in ML models and RL or

Qualifications

• Education: Excellence in Harvard coursework in CS, ECE, Math, or related major. Exceptional candidates with strong research contributions encouraged.
• Experience: Publishing in top-tier AI/ML conferences (e.g., NeurIPS, ICML, ICLR) or equivalent internship with an AI research lab.
• Technical: Expertise in training ML models, including deep learning, reinforcement learning or genetic algorithms.

Responsibilities

• 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.

Skills

Academic publishing in AI/ML

Deep learning

Reinforcement learning

Genetic algorithms

Education

Harvard CS/ECE/Math coursework excellence

Job description

Autoscience in the San Francisco Bay Area is seeking a Machine Learning Research Engineer for a full-time on-site role. You will work with the founder to develop autonomous research systems that ideate, experiment, and improve customer models, and collaborate with the engineering team to deploy production-ready systems.

Qualifying candidates have Harvard-level CS/ECE/Math excellence and a track record in AI/ML research, with publications in top conferences; strong training in ML models and RL or