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Remote Machine Learning Quant Jobs in New York (NOW HIRING)

Chasm Select

Senior Machine Learning Engineer

Manhattan, NY · On-site +1

$150K - $180K/yr

Remote (For Non-Local) or Hybrid (Local to NYC area) Position Summary: Join our mission to infuse ... Bachelor's or Master's degree in Computer Science, Machine Learning, or a related quantitative ...

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 ...

Inizio Partners

Machine Learning Engineer (GCP)

Manhattan, NY · Remote

$58.25 - $79.75/hr

Location- Remote Overview: As a GCP ML Engineer, you'll design, develop, and maintain machine learning pipelines and infrastructure on the Google Cloud Platform (GCP). You'll work closely with data ...

Finch Services

Machine Learning Engineer

Manhattan, NY · On-site +1

$180K - $280K/yr

As a Machine Learning Engineer at Finch, you'll own the full lifecycle of AI systems, from ... for a remote-first role -- this one is 4 days/week in our NYC office. Compensation The expected ...

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Remote Machine Learning Quant information

What is the difference between Remote Machine Learning Quant vs Remote Data Scientist?

AspectRemote Machine Learning QuantRemote Data Scientist
Required CredentialsAdvanced degrees in quantitative fields, certifications in machine learning or financeDegrees in data science, statistics, or related fields; certifications like CAP or DASCA
Work EnvironmentFinancial firms, hedge funds, or quantitative trading companiesTech companies, research institutions, or consulting firms
Industry UsageFinance, trading, hedge fundsTechnology, healthcare, marketing, finance
Common Search/ComparisonYesNo

Remote Machine Learning Quants focus on developing quantitative models for trading and investment strategies within financial firms, often requiring finance-specific knowledge. Remote Data Scientists work across various industries, applying data analysis and machine learning to solve diverse business problems. While both roles involve machine learning, Quants are more finance-oriented, whereas Data Scientists have broader industry applications.

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 Remote Machine Learning Quant jobs in New York? For Remote Machine Learning Quant jobs in New York, the most frequently searched job titles are:
What job categories do people searching Remote Machine Learning Quant jobs in New York look for? The top searched job categories for Remote Machine Learning Quant jobs in New York are:
What cities in New York are hiring for Remote Machine Learning Quant jobs? Cities in New York with the most Remote Machine Learning Quant job openings:
Remote Machine Learning Quant jobs near you
Infographic showing various Remote Machine Learning Quant job openings in New York as of June 2026, with employment types broken down into 86% Full Time, 6% Part Time, 4% Temporary, 3% Contract, and 1% Nights. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution.

Remote Machine Learning Engineer

Angenex

Jersey City, NJ • Remote

Other

This job post has expired today. Applications are no longer accepted.

Job description

Remote Machine Learning Engineer

Jersey City, NJ, United States

About the Job

We're seeking an outstanding ML Engineer to join our data team and help build out best-in-class machine learning solutions on our platform, powering innovative solutions in marketing & sales and commercial analytics.

Responsibilities

- Build and deploy the ML pipelines that power the company machine learning platform.

- Manage MLOps infrastructure to monitor and optimize models.

Qualifications

Experience:

1+ years of professional experience as a Machine Learning Engineer or production-focused Data Scientist.

Proficiency across topics in machine learning and statistics.

Fluency in Python coding as well as data manipulation (SQL, Spark, Pandas)

Broad familiarity with the Python ecosystem and common libraries including Scikit-Learn, XGBoost, PyTorch, Keras, Tensorflow, Pandas, and common ML cloud services.

Familiarity with CNNs, RNN, LSTMs, and the latest research trends.

Experience implementing, deploying, and maintaining production machine learning systems.

Experience monitoring and optimizing model performance.

Experience with Linux, Docker and AWS, and basic development operations.

Advanced degree in computer science, mathematics, statistics or related area of study strongly preferred.

Apply