Quantitative Development - DevOps Engineer

The Central Liquidity Strategies (CLS) business manages a number of portfolios and products designed to optimize the firm’s trading and execution approach by providing internal liquidity solutions for portfolio managers on both a risk and agency basis.

We are seeking a highly driven, results-oriented, and opinionated dev ops leader with experience in handling research infrastructure, deploying critical applications, and operating on large amounts of data to create battle-tested infrastructure and improve the research development experience.

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• Leadership: the candidate will design and implement infrastructure, and advise on and enforce best practices to maximize research and development velocity
  
• Research: the candidate is expected to keep up with the state-of-the-art tools that are being used in the field and continuously evaluate what the best tools and practices are for our use cases
  
• Machine Learning Operations (MLOps) + Development Experience (DevEx):
  
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  • create dependable and reproducible polyglot (Python, native extensions, CUDA) environments for rapidly iterating research projects that can be easily deployed to prod
    
  • Enforce best practices and packaging standards for large research codebases
    
  • Work with the cloud to help scale research jobs
    
  
  
• Infrastructure automation:
  
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  • develop CI/CD pipelines for research processes and live trading apps
    
  • develop robust monitoring solutions for infrastructure and deployed applications
    
  • automate recurring jobs with tools like Airflow/Prefect
    
  
  
• Performance engineering:
  
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  • Be familiar with best practices for profiling, monitoring performance to assist with performance investigations
    
  • Develop solutions that empower researchers and developers to understand the performance of their code
    
  
  

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• Experience: 7 years + of experience with research focused DevOps (HPC, ML research, quant research) and experience with high-availability production deployments
  
• Strong communications skills and ability to work with many stakeholders in a team environment
  
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• Leadership skills: ability to work with constraints, make decisions under time pressure, and own your work
  
• Development skills: Experience writing clean, robust, and testable code for automating processes pertaining to infrastructure management and deployment
  
• Systems knowledge:
  
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  • familiarity with Linux internals
    
  • understanding of package management, how software is deployed on systems
    
  
  
• Python:
  
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  • Strong understanding of Python internals
    
  • Familiarity with the latest standards in the packaging ecosystem (uv), build tools like hatchling
    
  
  
• Familiarity with tools like: Nix, Conda, Pixi, Kubernetes and containers