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Machine Learning Researcher Jobs in New York (NOW HIRING)

Quanta Search

Machine Learning Engineer

Manhattan, NY · On-site

Our client is a process driven investment management group consisting of a team of researchers ... Machine Learning Engineers build production grade machine learning algorithms that operate in real ...

Oxman

Machine Learning Research Engineer

New York, NY · On-site

$142K - $184K/yr

D. or equivalent experience in Computer Science, Machine Learning, Operations Research, or related fields. * Demonstrated experience working in cross-functional teams bridging ML research with ...

Quanta Search

Machine Learning Engineer

Manhattan, NY · On-site

Our client is a process driven investment management group consisting of a team of researchers ... Machine Learning Engineers build production grade machine learning algorithms that operate in real ...

Forhyre

Machine Learning Engineer

New York, NY

Research and implement appropriate ML algorithms and tools * Develop machine learning applications according to requirements * Select appropriate datasets and data representation methods * Run ...

Point72

Machine Learning Engineer

New York, NY · On-site

The core of our effort is rigorous research into a wide range of market anomalies, fueled by our ... Role/Responsibilities: We are seeking a Machine Learning Engineer to join the High Frequency ...

GPTZero

Machine Learning Intern

New York, NY · On-site

What we're looking for At GPTZero, we ensure that machine learning models are created for the ... The ideal candidate is someone who has a history of ML research, possesses a great product sense ...

Goodfire

Machine Learning Engineer

Manhattan, NY · On-site

Goodfire is a research company focused on understanding and designing AI systems. The Machine Learning Engineer will play a central role in building the platform for training, evaluating, and ...

Spotify

Machine Learning Engineer

New York, NY · On-site +1

$170K - $212K/yr

Work with Data and ML Engineers to support transitioning machine learning models from research and development into production * Implement and monitor model success metrics, diagnose issues, and ...

Spotify

Machine Learning Engineer

New York, NY · On-site +1

$170K - $212K/yr

Work with Data and ML Engineers to support transitioning machine learning models from research and development into production * Implement and monitor model success metrics, diagnose issues, and ...

Kitware

Machine Learning Engineer

Minneapolis, MN · On-site

$85K - $125K/yr

Kitware is a leader in advanced research and algorithm development in artificial intelligence (AI ... Machine learning experience using visual data * Understanding of a variety of machine learning ...

Hang

Machine Learning Engineer

New York, NY · On-site +1

Research and Innovation: Stay up-to-date with the latest developments in machine learning and AI, and explore new techniques and technologies that could benefit Hang. * Technical Leadership: Provide ...

Jane Street

Machine Learning Engineer

New York, NY · On-site

Machine learning is a critical pillar of Jane Street's global business. Our ever-evolving trading ... Your work will also focus on enhancing research workflows to tighten our feedback cycles.

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All JobsMachine Learning Researcher JobsMachine Learning Researcher Jobs in New York

Machine Learning Researcher information

See New York salary details

$32.8K

$123.7K

$180K

How much do machine learning researcher jobs pay per year?

As of Jul 4, 2026, the average yearly pay for machine learning researcher in New York is $123,737.00, according to ZipRecruiter salary data. Most workers in this role earn between $73,300.00 and $168,500.00 per year, depending on experience, location, and employer.

What are some common challenges Machine Learning Researchers face when transitioning from academic research to industry roles?

Machine Learning Researchers often find that transitioning to industry involves adapting to faster project timelines, collaborative workflows, and a focus on scalable, real-world solutions rather than theoretical advances alone. In industry, you'll likely work closely with cross-functional teams, such as software engineers and product managers, to ensure models are both practical and maintainable. Balancing innovation with business objectives, handling production constraints, and communicating complex findings to non-technical stakeholders are some of the key challenges you may encounter.

What are the key skills and qualifications needed to thrive as a Machine Learning Researcher, and why are they important?

To thrive as a Machine Learning Researcher, you need deep expertise in mathematics, statistics, programming (typically Python), and a strong academic background in computer science or related fields. Familiarity with frameworks like TensorFlow or PyTorch and experience with tools for data analysis and model development are standard, often supported by advanced degrees or relevant certifications. Critical thinking, creativity, and effective communication are vital soft skills for developing novel solutions and collaborating across interdisciplinary teams. These skills enable researchers to design innovative algorithms, validate models rigorously, and contribute impactful advancements in the field.

What is the difference between Machine Learning Researcher vs Data Scientist?

AspectMachine Learning ResearcherData Scientist
Required CredentialsAdvanced degrees in CS, ML, or related fields; research experienceDegree in CS, statistics, or related; strong analytical skills
Work EnvironmentResearch labs, academia, R&D departmentsBusiness environments, tech companies, consulting
Employer & Industry UsageUniversities, research institutions, tech firmsCorporations, startups, finance, healthcare
Common Search & ComparisonFocus on theoretical ML advancementsFocus on data analysis & business insights

While both roles involve working with data and algorithms, Machine Learning Researchers primarily focus on developing new algorithms and advancing ML theory, often in research or academic settings. Data Scientists apply these techniques to analyze data, generate insights, and support business decisions in industry environments.

What does a Machine Learning Researcher do?

A Machine Learning Researcher designs, develops, and tests algorithms and models that allow computers to learn from and make decisions based on data. They often work on advancing the field by exploring new methods, improving existing algorithms, and publishing their findings. These researchers collaborate with engineers and data scientists to apply their research to practical problems in areas like computer vision, natural language processing, and robotics. Their work typically involves a combination of mathematics, statistics, programming, and experimentation.
What are the most commonly searched types of Machine Learning Researcher jobs in New York? The most popular types of Machine Learning Researcher jobs in New York are:
What are popular job titles related to Machine Learning Researcher jobs in New York? For Machine Learning Researcher jobs in New York, the most frequently searched job titles are:
What job categories do people searching Machine Learning Researcher jobs in New York look for? The top searched job categories for Machine Learning Researcher jobs in New York are:
Machine Learning Researcher jobs near you

Machine Learning Engineer

Quanta Search

Manhattan, NY • On-site

Full-time

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

Job description

Our client is a process driven investment management group consisting of a team of researchers, traders and technologists who harness and apply the power of technology and automation to identify, model and trade global financial markets. This division offers an array of quantitative investment fund products to its clients.
They are seeking candidates with exceptional academic credentials to join their team and participate in and support of the firm's efforts in the research, trading and production processes.
They look for candidates who are eager to make an impact by doing real, hands-on research and development. Candidates must possess exceptional knowledge of mathematical and statistical methods as well as a proven ability to solve complex problems. A desire to work with large data sets and apply creative thinking is required. Successful candidates will also have deep interest in learning about trading and the financial markets.
They offer a supportive environment that fosters independent thought in a collegial, results oriented, work setting. Researchers and developers there are passionate about their work, model building, data and technology.
You are curious and intellectually driven to succeed. You'll be provided with the tools, resources and training required to satisfy that curiosity and passion, leading them to new insights and discoveries. Their process driven approach enables these insights to be thoroughly tested in a systematic fashion and ultimately, if confirmed, integrated into the portfolio.
Role:
Machine Learning Engineers build production grade machine learning algorithms that operate in real time or at scale. They have a very deep understanding of machine learning algorithms and cloud computing. Machine Learning Engineers should be comfortable with data engineering and should have an interest in the data science.
What they will do:
They will be responsible for their production grade signal generation and ML systems. They can act as data scientists, but should be comfortable pushing their algorithms, models, and signals into production.
Minimum Requirements:
  • Strong understanding of statistical analysis and computational modelling.
  • Strong understanding of algorithms and data structures.
  • Familiar with map reduce and big data processing (Spark, Hadoop, DataFlow, etc).
  • TensorFlow (or another GPU integrated deep learning library).
  • Deep understanding of machine learning algorithms.
  • Deep understanding of numerical optimization.
  • Strong understanding of data structures and algorithms.

Plus, but not required:
  • Previous experience in tech industry (GOOG, AMZN, FB, NFLX, Spotify, etc).
  • Experience building industrial grade ETL pipelines.
  • Experience building frontend systems.
  • Familiarity with dashboards and other visualization tools.
  • Ability to derive generalization bounds for common ML algorithms.
  • Experience developing new machine learning algorithms.

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