Senior Research Engineer - Voleon Securities

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.

As a Senior Research Engineer embedded within our first quant strategy team, you will own the team’s research infrastructure and overnight pipelines. You will work closely with both researchers on the team and engineers who oversee our trading execution system. You will be expected to help optimize machine learning training and testing environments, architect and maintain data pipelines and job graphs, and help deploy new machine learning driven market making strategies to production. This role has the potential to become a lead research engineer across Voleon Securities.

Your Team

We look for responsible people with a passion for solving problems. You’ll work in a collaborative environment that encourages creative thinking and efficient implementation. We embrace experimentation. You’ll work alongside experienced engineers recruited from leading technology companies and universities. You and your team will collaborate closely with top machine learning researchers.

Responsibilities

• Develop and optimize ML driven research infrastructure (Python, Pytorch, Jax)

• Optimize training and inference for machine learning models (Pytorch, Jax)

• Deploy machine learning models from research into production

• Develop tooling to integrate data from diverse exchanges and sources

• Improve the resilience and performance of our trading systems

• Collaborate with external engineering support teams at Voleon, including the trading execution team

• Mentor and develop other engineers on the team, and share your practices and knowledge with the team and company

Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field (or equivalent experience)

• 5+ years of software engineering experience, with a strong background in backend systems, distributed computing, or data infrastructure

• Experience in programming languages such as Python, Go, and C++

• Understanding of database technologies (Postgres, MySQL, Cassandra, DynamoDB, SQLite, DuckDB or MongoDB) and experience with APIs (REST/gRPC)

• Strong problem-solving skills, with a focus on delivering high-quality, maintainable, and well-documented solutions

• Excellent communication and collaboration skills; ability to work closely with both engineering and research teams

Preferred Qualifications

• Expertise in building and optimizing data pipelines

• Experience with profiling and performance optimizations on highly available systems

• Expertise implementing deep learning and RL frameworks in Pytorch or Jax

• Experience optimizing research infrastructure and providing engineering support to researchers

• Experience building a quantitative market-making strategy

• Experience bringing machine learning models into production

• Experience leading cross team collaborations or working cross functionally

“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  to submit your referral. For more details regarding eligibility, terms and conditions please make sure to review the .

Equal Opportunity Employer

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.