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Remote Machine Learning Quant Jobs in Union City, NJ

OptionMetrics

Quant Associate

New York, NY · On-site +1

$130K - $160K/yr

Exposure to machine learning techniques or predictive modeling. * Internship or research experience within quantitative finance, financial engineering, or capital markets. * Intellectual curiosity, a ...

OptionMetrics

Quant Associate

New York, NY · On-site +1

$130K - $160K/yr

Exposure to machine learning techniques or predictive modeling. * Internship or research experience within quantitative finance, financial engineering, or capital markets. * Intellectual curiosity, a ...

Career Renew

Senior Machine Learning Engineer

New York, NY · Remote

$165K - $225K/yr

Career Renew is recruiting for one of its clients a Senior Machine Learning Engineer - this is a fully remote role for US/Canada based candidates. Salary range: 165-225K USD yearly plus benefits plus ...

Etsy

Senior Staff Machine Learning Engineer

Brooklyn, NY · On-site +1

$245K - $319K/yr

This position will be in Brooklyn, NY or for remote candidates based in the United States. Etsy is ... A foundational and practical understanding of machine learning principles and the critical steps ...

Etsy

Senior Staff Machine Learning Engineer

New York, NY · On-site +1

$245K - $319K/yr

This position will be in Brooklyn, NY or for remote candidates based in the United States. Etsy is ... A foundational and practical understanding of machine learning principles and the critical steps ...

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Showing results 21-40

All JobsMachine Learning Quant JobsRemote Machine Learning Quant JobsRemote Machine Learning Quant Jobs in Union City, NJ

Remote Machine Learning Quant information

See Union City, NJ salary details

$12K

$141.7K

$216.4K

How much do remote machine learning quant jobs pay per year?

As of Aug 21, 2026, the average yearly pay for remote machine learning quant in Union City, NJ is $141,719.00, according to ZipRecruiter salary data. Most workers in this role earn between $127,300.00 and $151,400.00 per year, depending on experience, location, and employer.

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 job categories do people searching Remote Machine Learning Quant jobs in Union City, NJ look for?

The top searched job categories for Remote Machine Learning Quant jobs in Union City, NJ are:

What cities near Union City, NJ are hiring for Remote Machine Learning Quant jobs?

Cities near Union City, NJ with the most Remote Machine Learning Quant job openings:

Remote Machine Learning Quant jobs near you

Sr. Lead Machine Learning Engineer/Remote

Apetan Consulting llc

Paterson, NJ • Remote

$80 - $150/hr

Contractor

Re-posted 6 days ago

Job description

Sr. Lead Machine Learning EngineerLocation-RemoteJob Summary

The Sr. Lead Machine Learning Engineer is responsible for leading the design, development, deployment, and optimization of machine learning solutions that drive business value. This role combines technical expertise, strategic leadership, and cross-functional collaboration to build scalable AI/ML systems, mentor engineering teams, and guide the organization's machine learning initiatives.

Key Responsibilities
  • Lead the development and deployment of machine learning models and AI-driven solutions.
  • Design scalable ML architectures, pipelines, and production-ready systems.
  • Collaborate with data scientists, software engineers, product managers, and business stakeholders to define and deliver ML solutions.
  • Oversee data preparation, feature engineering, model training, evaluation, and monitoring processes.
  • Optimize model performance, scalability, reliability, and operational efficiency.
  • Establish best practices for MLOps, model governance, testing, and deployment.
  • Conduct code reviews and provide technical leadership and mentorship to engineering teams.
  • Evaluate emerging AI/ML technologies and recommend innovative solutions.
  • Ensure compliance with security, privacy, and responsible AI standards.
  • Support production systems by troubleshooting and resolving complex ML-related issues.
  • Drive technical roadmaps and contribute to strategic AI initiatives.
Required Qualifications
  • Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, or a related field.
  • 8+ years of software engineering experience, including 5+ years in machine learning engineering.
  • Strong proficiency in Python and machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.
  • Experience building and deploying machine learning models in production environments.
  • Strong knowledge of data structures, algorithms, statistics, and machine learning techniques.
  • Experience with cloud platforms such as AWS, Azure, or Google Cloud.
  • Knowledge of MLOps tools, CI/CD pipelines, and model monitoring practices.
  • Excellent leadership, communication, and problem-solving skills.
Preferred Qualifications
  • Master’s degree or Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
  • Experience with large-scale distributed systems and big data technologies.
  • Knowledge of Generative AI, Large Language Models (LLMs), NLP, computer vision, or recommendation systems.
  • Experience with Kubernetes, Docker, and cloud-native architectures.
  • Prior experience leading technical teams and enterprise AI initiatives.