The Voleon GroupRemote
Senior Research Engineer - Voleon Securities
United States
Full-time
3 days ago
$225,000 - $310,000 USD
H1B Sponsor Likely
Key skills
Machine LearningPythonData PipelinesBackend SystemsDistributed ComputingDeep LearningAPIsCollaboration SkillsProblem-Solving SkillsC++CGoAIMLPyTorchJAXCassandragRPCDynamoDBPostgresMySQLMongoDBSQLiteCommunicationCollaboration
About this role
The Voleon Group is an early-stage market maker focused on applying AI and machine learning techniques to finance. As a Senior Research Engineer, you will own the research infrastructure and collaborate with researchers and engineers to optimize machine learning environments and deploy market-making strategies.
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
- 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