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Machine Learning Quant Jobs in New York (NOW HIRING)

Root Access Inc

Machine Learning Engineer

New York, NY · On-site

D. in Computer Science, Mathematics, EE, Physics, or a related quantitative field with a focus on Scientific Machine Learning (SciML). * Deep Learning Frameworks: 4+ years of expert-level experience ...

Virtu Financial

Machine Learning Researcher

New York, NY

$200K - $300K/yr

Virtu is a quantitative trading firm that uses cutting-edge models and infrastructure to provide liquidity to the global markets. As a Machine Learning Researcher at Virtu, you'll pursue high-impact ...

Virtu Financial

Machine Learning Researcher

New York, NY · On-site

$200K - $300K/yr

Virtu is a quantitative trading firm that uses cutting-edge models and infrastructure to provide liquidity to the global markets. As a Machine Learning Researcher at Virtu, you'll pursue high-impact ...

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 ...

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Machine Learning Quant information

See New York salary details

$57.4K

$130.4K

$215K

How much do machine learning quant jobs pay per year?

As of Jul 28, 2026, the average yearly pay for machine learning quant in New York is $130,371.00, according to ZipRecruiter salary data. Most workers in this role earn between $85,900.00 and $166,800.00 per year, depending on experience, location, and employer.

What is a Machine Learning Quant job?

A Machine Learning Quant is a specialist in quantitative finance who applies machine learning techniques to develop trading strategies, manage risk, and analyze financial data. They leverage statistical models, deep learning, and reinforcement learning to identify patterns in market data and optimize predictions. This role typically involves programming in Python or C++, working with large datasets, and collaborating with traders and researchers. Machine Learning Quants are employed by hedge funds, investment banks, and proprietary trading firms to gain a competitive edge in financial markets.

What are the key skills and qualifications needed to thrive in the Machine Learning Quant position, and why are they important?

To thrive as a Machine Learning Quant, you need strong skills in quantitative analysis, programming (often in Python or C++), statistical modeling, and a solid foundation in applied mathematics, typically supported by a degree in a quantitative field such as mathematics, physics, computer science, or engineering. Familiarity with machine learning frameworks (like TensorFlow or PyTorch), financial data platforms, and certifications such as CFA or advanced degrees can be advantageous. Critical thinking, collaboration, and clear communication are key soft skills that enhance effectiveness in working with both technical and non-technical stakeholders. These competencies are crucial for building and validating models that inform high-stakes financial strategies and deliver value in fast-paced trading environments.

What are typical daily responsibilities for a Machine Learning Quant in a financial firm?

As a Machine Learning Quant, your day often involves researching and developing predictive models using large financial datasets, backtesting quantitative strategies, and optimizing algorithms for speed and accuracy. You'll collaborate closely with traders, data engineers, and other quants to implement models in live trading environments and refine them based on performance feedback. Regular activities also include monitoring new data sources, adjusting to changes in the market, and documenting your methodologies for regulatory or team review. This multidisciplinary work environment offers the opportunity to continuously learn and directly impact trading outcomes.

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:
What are popular job titles related to Machine Learning Quant jobs in New York? For Machine Learning Quant jobs in New York, the most frequently searched job titles are:
What job categories do people searching Machine Learning Quant jobs in New York look for? The top searched job categories for Machine Learning Quant jobs in New York are:
Machine Learning Quant jobs near you
Infographic showing various Machine Learning Quant job openings in New York as of July 2026, with employment types broken down into 1% As Needed, 74% Full Time, 23% Part Time, 1% Temporary, and 1% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $130,371 per year, or $62.7 per hour.

Machine Learning Researcher / Machine Learning Engineer

Anson McCade

Manhattan, NY • On-site

$200K/yr

Full-time

Posted 11 days ago

Job description

$200,000 - 2,000,000 USD
Onsite WORKING
Location: New York, New York - United States Type: Permanent
ML Researcher / ML Engineer
I am working with one of the world's leading quantitative trading firms, recognised for combining cutting-edge technology, quantitative research, and machine learning to solve some of the most complex challenges in global financial markets. Renowned for its research-driven culture and engineering excellence, the firm continues to make significant investments in next-generation machine learning capabilities that directly enhance trading performance and business outcomes.
As part of the continued expansion of its Machine Learning platform, the firm is looking to hire exceptional Machine Learning Researchers and Machine Learning Engineers to join several high-performing teams working across large-scale machine learning, deep learning, distributed systems, and production ML infrastructure.
The Opportunity
This is an opportunity to work alongside some of the industry's leading researchers and engineers, developing advanced AI models and production-scale machine learning systems that are deployed directly into live trading environments.
Depending on your experience and interests, you may focus on areas including:
  • Large Language Models (LLMs)
  • Foundation model training and optimisation
  • Agentic AI systems
  • Applied machine learning research
  • Model evaluation and post-training optimisation
  • Distributed systems and AI infrastructure
You'll tackle challenging mathematical and engineering problems while building scalable, production-ready AI solutions in a highly collaborative and research-driven environment.
Requirements
Successful candidates will typically possess:
  • Strong experience in Machine Learning, Deep Learning, Large Language Models, AI Infrastructure, or Distributed Systems
  • Excellent programming skills in Python and/or C++
  • Experience developing and deploying production-grade machine learning systems
  • A strong mathematical foundation and exceptional problem-solving ability
  • A passion for solving technically demanding challenges in a fast-paced environment
Why Join?
This firm offers the opportunity to work on some of the most advanced AI and machine learning challenges in the financial industry, alongside world-class researchers, engineers, and quantitative professionals.
The compensation package is exceptionally competitive, with top performers receiving industry-leading total compensation, complemented by outstanding career progression, access to cutting-edge technology, and the opportunity to make a direct impact on live trading systems from day one.

Apply