Responsibilities
Qualifications

- Architecting and developing the next generation of Company's machine learning research platform, with an emphasis on scalability, reliability, observability, and reproducibility
- Building infrastructure that enables large-scale experimentation, model training, and simulation across on-premises HPC and multi-cloud environments
- Partnering closely with quantitative researchers to understand evolving research workflows and translate them into robust platform capabilities
- Designing and optimizing distributed training pipelines for high-throughput, GPU-accelerated workloads
- Improving experiment management, model versioning, artifact tracking, and data lineage to ensure transparent and reproducible research
- Developing tools and frameworks that streamline feature engineering, dataset generation, and large-scale backtesting
- Leading initiatives to improve compute efficiency, resource scheduling, and workload isolation across heterogeneous environments
- Enhancing platform observability, including metrics, logging, tracing, and debugging capabilities tailored to ML workloads
- Supporting rapid iteration by implementing features and fixes on tight timelines while maintaining high engineering standards
- Contributing to long-term architectural decisions that enable the platform to scale with increasing data volumes and model complexity
Qualifications
- 2+ years of experience designing and building large-scale distributed systems, ideally in support of research or data-intensive workloads
- Strong programming experience in Python, with a focus on writing clean, maintainable, and high-performance code
- Experience developing and operating applications on Linux-based HPC clusters and/or cloud platforms
- Solid understanding of distributed computing concepts, parallel processing, and resource management
- Experience with GPU-based workloads and familiarity with modern ML frameworks (e.g., PyTorch, TensorFlow, JAX)
- Experience optimizing data pipelines and handling large-scale structured and unstructured datasets
- Strong troubleshooting skills with the ability to debug complex, cross-layer system issues
- Ability to work independently in a fast-paced, research-driven environment
- Strong communication skills and experience collaborating directly with researchers or data scientists

Job ID PR/595853
We support the Financial Sciences & Services industry with talent that can truly shape the future of a business.
Whether that be Quantitative Analyti...
More Jobs From Selby Jennings
Selby Jennings
Chicago, United States
Selby Jennings
Chicago, United States
Selby Jennings
London, United Kingdom
Selby Jennings
London, United Kingdom
Selby Jennings
Manhattan, United States
Selby Jennings
London, United Kingdom
Selby Jennings
Manhattan, United States
Boost your career
Find thousands of job opportunities by signing up to eFinancialCareers today.More Jobs Like This
Westbury Partners
Sydney, Australia