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Virtu Financial

Makes markets in stocks and sells trading software

Machine Learning Engineer

Platform EngineeringConfirmed live in the last 24 hours
Full-timeNew York, NY, USA$200k - $300kIn-person

About the Job

Requirements

  • At least 5 years of experience in machine learning engineering, research infrastructure, or high-performance computing environments.
  • Strong Python engineering skills, including writing clean, maintainable, well-tested code.
  • Experience building or operating distributed training infrastructure, with working knowledge of how collective communication libraries such as NCCL and Horovod behave at scale.
  • Practical experience with experiment tracking systems and knowledge of effective research infrastructure.
  • Comfort working across the Linux systems stack, including storage, networking, and job scheduling.
  • Ability to work closely with researchers and engineers across disciplines.
  • Intellectual curiosity and self-direction, including proactively identifying problems worth solving.

Responsibilities

  • Design and build experiment tracking, job orchestration, and reproducibility infrastructure so researchers can iterate quickly, compare runs reliably, and recover from failures without losing work.
  • Create tools for all stages of the simulation lifecycle, including historical back-tests and production monitoring, and add new features to simulators.
  • Own visibility into GPU cluster utilization by tracking allocation, surfacing bottlenecks, and ensuring compute investments are used effectively.
  • Diagnose and resolve performance issues across training pipelines, including data-loading throughput, storage I/O, GPU utilization, and inter-node communication in distributed training runs.
  • Build and maintain data pipelines that move financial data from storage into training workflows efficiently, with strong guarantees on correctness and versioning.
  • 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, from tooling improvements to infrastructure changes.
  • Collaborate with infrastructure engineers on capacity planning, cloud/on-premises tradeoffs, and tooling decisions.
  • Stay current with developments in machine learning infrastructure tooling and bring relevant ideas and tools into the stack where they create value.

Desired Qualifications

  • Exposure to C++ in a performance-sensitive context.
  • Experience with on-premises compute environments and job orchestration tools such as Slurm.
  • Familiarity with GPU profiling tools such as Nsight Systems and 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 such as Prefect or Dagster.
  • Prior experience in environments with high-stakes, large-scale time-series data, including quantitative finance or algorithmic trading.
  • Experience contributing to or extending open-source machine learning frameworks or infrastructure tooling.

About the Company

Virtu Financial

Makes markets in stocks and sells trading software

Virtu Financial runs automated systems that stand ready to buy or sell stocks, options, bonds, currencies, and cryptocurrencies worldwide, so investors and brokers can trade instantly. In 2014, its filing to go public revealed that it had lost money on just one of 1,238 trading days. Its computers post buy and sell prices on exchanges and fill orders that retail brokers send it, earning the small gap between the two prices across huge volumes. A separate client business runs POSIT, a private venue for matching large stock orders, and sells trading software to fund managers for commissions and fees. Virtu was founded in 2008, grew by buying rival market maker KCG in 2017, and is based in New York City.

Company size
1,001-5,000
Company stage
IPO
Headquarters
New York City, New York
Founded
2008

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