Member of Research Staff, Reinforcement Learning, Voleon Securities
- Location
- Berkeley, CA (Remote) · On-site
- Job type
- Full-time
- Level
- Mid-level
- Education
- Doctorate
- Listed
- 31 days ago
Skills & highlights for this role
- reinforcement learning
- optimal control
- Python
- GPU computing
Also useful
- statistical machine learning
- financial markets
About the role
Voleon Securities, a new business within the Voleon Group, provides liquidity in securities markets. We apply state-of-the-art AI/ML techniques to construct our liquidity-provision strategies. For nearly two decades, our affiliate Voleon Capital Management has led the hedge fund industry and worked at the frontier of applying AI/ML to investment management, becoming a multibillion-dollar asset manager. Voleon Securities builds on Voleon’s deep real-world experience applying ML to financial markets.
Voleon Securities is looking to add an experienced and creative reinforcement learning researcher to our growing ML research group. We welcome researchers with both strong theoretical foundations and experience developing and scaling RL in industrial settings. Financial applications of RL are challenging and demand new methods that go beyond the academic state-of-the-art; it is critical candidates have a deep understanding of the field to draw inspiration for new methodology.
This is a chance to join the initial buildout of a fully modern securities business rooted in the frontier of AI/ML and statistics. Your colleagues will include internationally recognized experts in artificial intelligence and machine learning research as well as highly experienced finance and technology professionals.
As a Member of Research Staff, you will work at the forefront of modern statistical machine learning. Your research colleagues across Voleon have collectively published hundreds of academic articles in top-tier venues on machine learning, systems, and theory, and we meet regularly to stay current on the latest academic research and share ideas. Founded in 2007 by two leading scientists, Voleon supports a culture of curiosity, collegiality, and creativity.
Your work will focus on financial market prediction and portfolio optimization. The behavior of financial markets is noisy and violates a number of classical statistical assumptions, and we’ve spent over a decade pioneering scientific advances in the application of machine learning techniques to this domain. You will work with a complex and diverse array of datasets to implement and iterate on predictive models. Predicting financial markets is an enduringly hard problem, but results are immediate and unambiguous.
Years of academic training has prepared you for this moment. You won’t just conduct research, you’ll apply it on a daily basis, working with a team across the entire life cycle of applied research problems. Your work will span from basic research to productizing solutions and validating their efficacy in live trading.
- Relocation and work visa eligibility for qualified candidates
Responsibilities
- Develop a rich understanding of Voleon’s challenges and methodologies and propose RL research innovations and experiments to build, maintain and optimize the models that govern our trading strategy
- Prepare and analyze new datasets to assess their predictive efficacy
- Develop, validate, and implement new models in production
- Design and conduct experiments to improve simulations and evaluate the success of new models in a live environment
- Communicate and collaborate effectively with other Members of Research Staff and Software Engineers at each stage, driving progress towards tangible outcomes
- Keep up to date on the latest RL academic research to identify novel approaches to explore for application to our domain
Requirements
- Background in reinforcement learning or optimal control with a strong track record of publishing RL papers in top tier conferences
- Evidence of strong mathematical abilities (e.g., publication record, graduate coursework, or competition placement)
- Interest in software development techniques and willingness to write production-level code (Python)
- Ability to solve large-scale computing problems with GPUs
- Eagerness to work in a fast paced and growing business
- Interest in financial applications is essential, but prior finance industry experience is not a pre-requisite
- Ph.D. level coursework is required, and a Ph.D. degree in a relevant field is preferred
“Friends of Voleon” Candidate Referral Program
If you have a great candidate in mind for this role and would like to have the potential to earn $15,000 if your referred candidate is successfully hired and employed by The Voleon Group, please use this form to submit your referral. For more details regarding eligibility, terms and conditions please make sure to review the Voleon Referral Bonus Program
Equal opportunity and legal notices
The Voleon Group is an Equal Opportunity employer. Applicants are considered without regard to race, color, religion, creed, national origin, age, sex, gender, marital status, sexual orientation and identity, genetic information, veteran status, citizenship, or any other factors prohibited by local, state, or federal law.
#LI-MD1
From The Voleon Group's careers page, first listed on Rolev.ai on October 10, 2026. Rolev.ai is not the employer.
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Common questions
Where is the Member of Research Staff, Reinforcement Learning, Voleon Securities job at The Voleon Group located?
Yes, this Member of Research Staff, Reinforcement Learning, Voleon Securities opening at The Voleon Group is listed as Berkeley, CA (Remote) (On-site). Always check The Voleon Group's application page for specific state eligibility or relocation policies.
What qualifications are required for Member of Research Staff, Reinforcement Learning, Voleon Securities at The Voleon Group?
For the Member of Research Staff, Reinforcement Learning, Voleon Securities role, The Voleon Group highlights a doctorate; experience with reinforcement learning, optimal control, Python, GPU computing. Rolev.ai can score your existing resume against these requirements and show any skill gaps before you apply.
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