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Machine Learning Engineer

Pay
$200,000–300,000/yearAnnual period assumed — pay source
Experience contributing to or extending open-source ML frameworks or infrastructure tooling Salary Range: $200,000 - $300,000 (salary range is exclusive of bonuses, benefits or other categories of compensation) 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.
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What you’ll work on

Full posting
  • Build experiment tracking, job orchestration, and reproducibility infrastructure

  • Track GPU cluster allocation and surface utilization bottlenecks

  • Diagnose and fix performance issues in distributed training pipelines

  • Build and maintain versioned data pipelines from financial data storage into training

  • Create tools for simulation lifecycle, including back-tests and production monitoring

From the employer’s posting
Design and build experiment tracking, job orchestration, and reproducibility infrastructure
Own visibility into GPU cluster utilization — track allocation, surface bottlenecks
Diagnose and resolve performance issues across training pipelines
Build and maintain data pipelines that move financial data from storage into training workflows efficiently
Create tools for all stages of the simulation lifecycle including historical back-tests and production monitoring
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Posting record

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Open 6 monthsWe first saw this posting 203 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.

Status in our records
Live
First seen by us
Apr 15, 2026203 days ago
Recorded sightings
143
Last seen by us
Nov 4, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

Higher than most similar jobs

$200K–$300K against $166K–$240K, the middle half of what similar US postings state.

From 1,279 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 203

Up longer than most. Similar jobs usually come down between day 6 and day 69.

From 4,347 similar postings that came down. Coming down is not always a hire.

Virtu Financial is hiring

2 open jobs

  • Its jobs tend to stay up a long time
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • C++
  • Java
  • Python
  • Prefect
  • Dagster
  • Polars
  • PyTorch
Where the posting names them
Virtu’s Research Technology team is looking for an experienced Machine Learning Engineer to join a small group of technologists whose primary function is building the infrastructure that powers our quantitative researchers. This is a unique opportunity to work at the intersection of machine learning and systematic trading — building tools that directly determine how fast our researchers can move, and how effectively our GPU cluster translates into research output. In this role, you will be responsible for the development of our ML research platform: the systems that manage data and compute, track experiments, and enable researchers to go from idea to result as efficiently as possible. You will work closely with quants and engineers alike and will play a central role in shaping how ML is done at the firm as we scale our capabilities. We mostly use Python, C++ and Java with a variety of open-source tools along with proprietary solutions. THE ROLE
- 5+ years of experience in ML engineering, research infrastructure, or HPC environments - Strong Python engineering skills — you write clean, maintainable, well-tested code that other engineers want to build on. Exposure to C++ in a performance-sensitive context is a plus - Experience building or operating distributed training infrastructure, with working knowledge of how collective communication libraries (NCCL, Horovod, or similar) behave at scale
- 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
- 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)
- 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

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About the role

We file this job under ML Engineer, by the work the posting describes.

ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.

Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.

A data scientist often works out which model to build; an ML engineer makes it run reliably in production.

US government figures for computer and information research scientists

Median yearly pay, May 2025
$140,300
Expected change, 2025 to 2035
21.8% more jobsagainst 3.5% for all jobs

The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.

Job description

View original posting ↗

Virtu’s Research Technology team is looking for an experienced Machine Learning Engineer to join a small group of technologists whose primary function is building the infrastructure that powers our quantitative researchers. This is a unique opportunity to work at the intersection of machine learning and systematic trading — building tools that directly determine how fast our researchers can move, and how effectively our GPU cluster translates into research output.

In this role, you will be responsible for the development of our ML research platform: the systems that manage data and compute, track experiments, and enable researchers to go from idea to result as efficiently as possible. You will work closely with quants and engineers alike and will play a central role in shaping how ML is done at the firm as we scale our capabilities. We mostly use Python, C++ and Java with a variety of open-source tools along with proprietary solutions.

 

THE ROLE

  • 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. Add new features to our simulators
  • Own visibility into GPU cluster utilization — track allocation, surface bottlenecks, and ensure our compute investment is being used effectively
  • Diagnose and resolve performance issues across training pipelines: 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 that reduce it — from tooling improvements to infrastructure changes
  • Collaborate with existing infrastructure engineers on capacity planning, cloud/on-prem tradeoffs, and tooling decisions — this is a collaborative environment, not a siloed one
  • Stay current with developments in ML infrastructure tooling and bring relevant ideas and tools into our stack where they create genuine value

THE CANDIDATE

  • 5+ years of experience in ML engineering, research infrastructure, or HPC environments
  • Strong Python engineering skills — you write clean, maintainable, well-tested code that other engineers want to build on. Exposure to C++ in a performance-sensitive context is a plus
  • Experience building or operating distributed training infrastructure, with working knowledge of how collective communication libraries (NCCL, Horovod, or similar) behave at scale
  • Practical experience with experiment tracking systems and strong opinions about what good research infrastructure looks like
  • Comfort working across the Linux systems stack — storage, networking, job scheduling — enough to follow a problem wherever it leads
  • Excellent communication skills and the ability to work closely with researchers and engineers across disciplines
  • Intellectually curious and self-driven — you proactively identify problems worth solving, not just problems you've been asked to solve

DESIRED, BUT NOT REQUIRED

  • 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

 

Salary Range: $200,000 - $300,000 (salary range is exclusive of bonuses, benefits or other categories of compensation)

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.

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Pay
Experience contributing to or extending open-source ML frameworks or infrastructure tooling Salary Range: $200,000 - $300,000 (salary range is exclusive of bonuses, benefits or other categories of compensation) 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.
Location & working pattern

New York

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