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Assistant Machine Learning Quant Jobs in New York

Virtu Financial

Machine Learning Engineer

New York, NY · On-site

$200K - $300K/yr

Virtu's Research Technology team is looking for an experienced Machine Learning Engineer to join a ... You will work closely with quants and engineers alike and will play a central role in shaping how ...

Virtu Financial

Machine Learning Engineer

New York, NY

$200K - $300K/yr

Virtu's Research Technology team is looking for an experienced Machine Learning Engineer to join a ... You will work closely with quants and engineers alike and will play a central role in shaping how ...

Nvidia

Senior Machine Learning Engineer

New York, NY · On-site

$114K - $157K/yr

Master's degree or PhD in Mathematics, Statistics, Machine Learning or related quantitative field (or equivalent experience). * 8+ years experience applying Machine Learning to operational systems.

New

Man Group

Principal Quant

New York, NY

Experience with Machine Learning techniques is a plus * PhD or exceptional Masters / Bachelors ... quantitative subject * Expertise in Python and Linux environments * Comfortable proficiency in C ...

RunSybil

Machine Learning Engineer

New York, NY · On-site

MS or PhD in a quantitative discipline is nice but certainly not required - strong bias for ... Understanding of both modern and classic machine learning techniques * Equally comfortable with ...

Zencastr

Senior Machine Learning Engineer (Remote)

New York, NY · On-site +1

$114K - $157K/yr

A postgraduate degree in Machine Learning, Mathematics, Computer Science, or a related quantitative field * 5 + years experience in Python * 3+ years experience in machine learning research, with a ...

Chasm Select

Senior Machine Learning Engineer

Manhattan, NY · On-site +1

$150K - $180K/yr

Bachelor's or Master's degree in Computer Science, Machine Learning, or a related quantitative field. * Minimum 2 years of experience in industry with a strong focus on ML solutions development and ...

Chasm Select

Senior Machine Learning Engineer

Manhattan, NY · On-site

$150K - $180K/yr

Bachelor's or Master's degree in Computer Science, Machine Learning, or a related quantitative field. * Minimum 2 years of experience in industry with a strong focus on ML solutions development and ...

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Assistant Machine Learning Quant information

What is an assistant machine learning quant?

Assistant Machine Learning Quants are entry-level professionals in quantitative finance who support senior quants by applying machine learning techniques to analyze financial data, build predictive models, and develop trading strategies. Their responsibilities often include data cleaning, feature engineering, model selection, and performance evaluation. They work closely with quantitative researchers and traders to improve algorithmic trading systems and risk management processes. This role typically requires strong programming skills, a solid understanding of machine learning concepts, and familiarity with financial markets.

How does an assistant machine learning quant typically collaborate with senior quants and data scientists on projects?

As an Assistant Machine Learning Quant, you will often work closely with senior quantitative researchers and data scientists by supporting model development, data preprocessing, and feature engineering tasks. You may contribute to brainstorming sessions, implement prototypes, and assist in backtesting trading strategies or risk models. This collaborative environment provides valuable mentorship opportunities and exposure to best practices in quantitative analysis and machine learning within the finance industry. Effective communication and a willingness to learn from senior team members are key to success in this role.

What are the key skills and qualifications needed to thrive as an assistant machine learning quant, and why are they important?

To thrive as an Assistant Machine Learning Quant, you need strong quantitative skills, a background in statistics or mathematics, and typically a degree in a STEM field. Familiarity with programming languages such as Python or R, experience with machine learning frameworks, and knowledge of financial modeling tools are essential. Strong problem-solving abilities, attention to detail, and effective communication are standout soft skills in this role. These competencies enable accurate model development, efficient data analysis, and clear collaboration with team members in high-stakes financial environments.
What are the most commonly searched types of Machine Learning Quant jobs in New York? The most popular types of Machine Learning Quant jobs in New York are:
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Infographic showing various Assistant Machine Learning Quant job openings in New York as of June 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.

Machine Learning Engineer

Virtu Financial

New York, NY • On-site

$200K - $300K/yr

Full-time

Re-posted 28 days ago

Job description

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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