About the company
Our client is a software company.
The role
Raydar is recruiting for this role on behalf of our client. Act as a senior individual contributor who defines and drives a research program on how machine learning systems keep improving after deployment. Collaborate with engineers to carry experimental results through to shipped features.
What you'll do
- Lead a new research program from the ground up, covering how models retain knowledge, adjust quickly and get better on their own.
- Guide technical direction as a senior contributor alongside a compact group of researchers and engineers.
- Turn promising ideas from the roadmap into running experiments quickly.
- Work with software and ML engineers to move findings into production, from building datasets through evaluation to integration into the product.
- Aim for meaningful advances and share results with the wider research community.
Requirements
What we're looking for
- A doctorate, or comparable hands-on experience, in a quantitative or technical discipline.
- About 3 to 7 years doing applied research, whether at a startup, a research lab or a large technology firm.
- A research background in models that learn continuously, adapt with little data, improve themselves or build memory. Work in reinforcement learning or agent systems alone does not meet this bar.
- Practical experience with post-training of large models, including supervised and reinforcement-based approaches.
- A history of turning research concepts into working production systems, ideally in an early-stage environment.
- Papers accepted at leading machine learning conferences or journals.
- Strong coding skills in Python, a major deep learning framework and large-scale multi-machine training.
- Energy for a fast-paced startup where you own outcomes.
- Ability to work on-site at the office.
Bonus points
- Prior time at a research lab, large technology company or leading AI developer.
- Experience applying post-training techniques to agents that handle long, multi-step tasks.
Benefits
Compensation and benefits
- Base salary: USD 200,000 to 400,000 per year
- Equity
Location and work model
- San Mateo, CA, United States
- On-site
- Full-time
Skills Required
- Doctorate or comparable hands-on experience in a quantitative or technical discipline
- Approximately 3 to 7 years of applied research experience
- Research background in continual learning, rapid adaptation, low-data learning, self-improvement, or memory-building models
- Practical experience with large-model post-training using supervised and reinforcement-based approaches
- Experience turning research concepts into working production systems
- Papers accepted at leading machine learning conferences or journals
- Strong coding skills in Python, a major deep learning framework, and large-scale multi-machine training
- Ability to work on-site at the office
- Experience at a research lab, large technology company, or leading AI developer
- Experience applying post-training techniques to agents handling long, multi-step tasks
What We Do
Raydar is a talent acquisition and business consulting firm that connects world-class and emerging talent with growing organizations. It supports companies through team development, strategic hiring, and customized growth solutions, helping clients recruit roles such as engineers, product managers, executives, legal counsel, and quantitative traders. Raydar focuses on understanding each organization’s needs, culture, and long-term goals to build high-impact teams.
