Virtu Financial is looking for a Machine Learning Engineer to develop the core ML research platform that powers our quantitative researchers. In this role, you will build the infrastructure for data, compute, experiment tracking, and simulation to enable efficient iteration and effective use of our GPU clusters.
What You'll Do
- Design and build experiment tracking, job orchestration, and reproducibility infrastructure.
- Create tools for all stages of the simulation lifecycle including historical back-tests and production monitoring.
- Own visibility into GPU cluster utilization — track allocation, surface bottlenecks, and ensure compute investment is used effectively.
- Diagnose and resolve performance issues across training pipelines: data loading, storage I/O, GPU utilization, and inter-node communication.
- Build and maintain data pipelines that move financial data into training workflows efficiently with strong correctness and versioning guarantees.
- Develop feature storage and retrieval patterns that support fast, reproducible access to training data at scale.
- Work directly with researchers to understand friction in their workflows and build solutions to reduce it.
- Collaborate with existing infrastructure engineers on capacity planning, cloud/on-prem tradeoffs, and tooling decisions.
- Stay current with developments in ML infrastructure tooling and bring relevant ideas into the stack.
What We're Looking For
- 5+ years of experience in ML engineering, research infrastructure, or HPC environments.
- Strong Python engineering skills — write clean, maintainable, well-tested code.
- Experience building or operating distributed training infrastructure with knowledge of collective communication libraries (NCCL, Horovod).
- Practical experience with experiment tracking systems and strong opinions about good research infrastructure.
- Comfort working across the Linux systems stack — storage, networking, job scheduling.
- Excellent communication skills and ability to work closely with researchers and engineers across disciplines.
- Intellectually curious and self-driven — proactively identify problems worth solving.
Nice to Have
- Experience with on-prem compute environments and job orchestration tools such as Slurm.
- Familiarity with GPU profiling tools (NSight Systems, PyTorch Profiler) and hands-on experience optimizing GPU memory or compute utilization.
- Experience with columnar data formats and high-performance data processing tools such as Parquet, Arrow, and Polars.
- Familiarity with workflow orchestration tools (Prefect, Dagster, or similar).
- Prior experience in environments with high-stakes, time-series data at scale. Open to Quantitative Finance, Algorithmic Trading, and Other.
- Experience contributing to or extending open-source ML frameworks or infrastructure tooling.
- Exposure to C++ in a performance-sensitive context.
Technical Stack
- Languages: Python, C++, Java
- Libraries & Systems: NCCL, Horovod, Slurm
- Data Tools: Parquet, Arrow, Polars
- Orchestration: Prefect, Dagster
Team & Environment
You will join a small group of technologists within the Research Technology team, working in a collaborative environment.
Benefits & Compensation
- Compensation range: $200,000 - $300,000
Virtu Financial is an equal opportunity employer, committed to a diverse and inclusive workplace, welcoming you for who you are and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.
