Senior Member of Research Staff, Optimization
Lead optimization research applying large-scale constrained optimization and ML to real-time trading decisions. Requires 5-10+ years experience, strong math/ML background, production coding skills, and PhD-level coursework.
About the job
Responsibilities
- Design, implement, and improve large-scale constrained optimization methods that determine trading decisions under forecasts, risk, costs, liquidity, and operational constraints
- Demonstrate strategic vision and perspective to oversee work that affects one or more complex systems and mission-critical areas
- Complete large scope, highly complex projects resulting in noteworthy improvements to product performance and risk management
- Develop a rich understanding of Voleon’s domain and methodologies
- Prepare and analyze new datasets to assess their predictive efficacy
- Develop, validate, and implement new models into production
- Design and conduct experiments to improve simulations and evaluate the success of new models in a live environment
- Build collaborative relationships cross-functionally and with key contacts outside own area of expertise, with the potential to serve as an external spokesperson for the organization
- Communicate and collaborate effectively with key stakeholders at each stage, facilitating meaningful discussions around complex issues and driving progress towards tangible outcomes
- Mentor other researchers and provide technical guidance, coaching, and feedback
- Keep up to date on the latest academic research to identify novel approaches to explore for application to our domain
- Contribute to Voleon's efforts to recruit exceptional talent
Requirements
- 5-10+ years of related experience in modern optimization techniques and algorithms directing key research projects and mentoring colleagues
- Experience with numerical methods, optimization solvers, mathematical programming, convex or nonconvex optimization
- Capability to run multiple projects simultaneously, exercising judgment in the methods, techniques, and evaluation criteria for determining results
- Ability to make well-reasoned design decisions, identifying and proactively potential issues, tradeoffs, risks, and the appropriate level of abstraction
- Proven success solving large-scale computing problems
- Expertise in modern statistical methods and machine learning with a track record as an applied researcher
- Evidence of strong mathematical abilities
- Strong skills in software development techniques and production level coding (Python and/or C++ preferred)
- Effective at communicating complex technical issues simply and transparently, including writing insightful documentation
- Ability to influence without requiring formal authority, with a proven track record of influence beyond your team
- Interest in financial applications is essential, but prior finance industry experience is not a prerequisite
- Ph.D. level coursework is required, and a Ph.D. degree in a relevant field is preferred
Preferred Qualifications
- Expertise in stochastic control, and reinforcement learning
Skills
Optimization, Numerical Methods, Optimization Solvers, Mathematical Programming, Convex Optimization, Nonconvex Optimization, Statistical Methods, Machine Learning, Python, C++, Stochastic Control, Reinforcement Learning
Similar jobs
ML Engineering jobs
Garner Health
New York, NY
Leads and builds a team of Applied Scientists developing production algorithmic systems for healthcare optimization, LLM applications, and member engagement. Requires 6+ years of relevant industry experience, strong technical judgment, and hands-on expertise across machine learning and optimization.
OpenAI
San Francisco, CA
Build production machine learning systems for model customization, post-training, evaluation, and AWS-native API integration. The role requires 7+ years of relevant engineering experience and expertise in deep learning, transformers, LLM fine-tuning, and production ML infrastructure.
OpusClip
Mountain View, CA
Leads a hands-on AI engineering team developing, evaluating, and deploying large-scale multimodal and video models. The role combines post-training, inference optimization, product experimentation, technical roadmap ownership, and people management.
Discord
United States
Leads Discord’s Safety ML team, setting technical direction and overseeing production machine learning systems for content understanding, account integrity, and platform abuse. Requires substantial machine learning and engineering management experience, hands-on technical depth, and experience delivering ML systems at scale.
Baselayer
San Francisco, CA
Senior AI Engineer responsible for production LLM agents that enrich business identity data through web discovery, verification, classification, and risk scoring. The role requires strong asynchronous Python, agent and evaluation expertise, browser automation, and experience operating AI systems in production.