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Senior Research Engineer - Voleon Securities

Builds and optimizes ML research infrastructure, deploys models to production for market-making strategies, and mentors engineers. Requires 5+ years backend experience, Python proficiency, and ML frameworks like PyTorch/Jax.

225k – 310kNew York, NYBerkeley, CAML EngineeringHybrid5+ YOE

About the role

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

Skills

PythonPyTorchJAXGoC++PostgresMySQLCassandraDynamoDBRestgRPC

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