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Machine Learning Research Engineer Jobs (NOW HIRING)

Optiver

Machine Learning Research Engineer

New York, NY

$224K/yr

Optiver is a seeking a Machine Learning Research Engineer to join our team, focusing on a pivotal AI initiative. This role would offer the opportunity to have significant impact across Machine ...

Optiver

Machine Learning Research Engineer

New York, NY · On-site

$200K/yr

Optiver is a seeking a Machine Learning Research Engineer to join our team, focusing on a pivotal AI initiative. This role would offer the opportunity to have significant impact across Machine ...

Roboflow

Machine Learning Research Engineer

The Machine Learning Research Engineer will develop novel methods and contribute to the research agenda, helping to translate innovative research into production systems that effectively address user ...

Roboflow

Machine Learning Research Engineer

The Machine Learning Research Engineer will develop novel methods and contribute to the research agenda, helping to translate innovative research into production systems that effectively address user ...

LLNL

Machine Learning Research Engineer

Livermore, CA

$146K - $222K/yr

We have an opening for Machine Learning Research experts to join our team and advance the ... Actively participate with project scientists and engineers in defining, planning, and formulating ...

LLNL

Machine Learning Research Engineer

Livermore, CA · On-site

$146K - $222K/yr

We have an opening for Machine Learning Research experts to join our team and advance the ... Actively participate with project scientists and engineers in defining, planning, and formulating ...

LLNL

Machine Learning Research Engineer

Livermore, CA · On-site

$9.8K/wk

We have an opening for Machine Learning Research experts to join our team and advance the ... Actively participate with project scientists and engineers in defining, planning, and formulating ...

Etched

Machine Learning Research Engineer

Cupertino, CA · On-site

$252K/yr

The Machine Learning Research Engineer will propose and conduct novel research to achieve results on Sohu, translating core mathematical operations into performant instruction sequences and ...

Oxman

Machine Learning Research Engineer

New York, NY · On-site

$142K - $184K/yr

EDEN is a digital design environment for engineering and designing ecosystems, modeling the flows ... Ph.D. or equivalent experience in Computer Science, Machine Learning, Operations Research, or ...

Etched

Machine Learning Research Engineer

Cupertino, CA · On-site

$252K/yr

The Machine Learning Research Engineer will propose and conduct research to optimize performance on Sohu, collaborating with hardware architects to develop software solutions that leverage the unique ...

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Machine Learning Research Engineer information

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$37K

$106K

$142.5K

How much do machine learning research engineer jobs pay per year?

As of Aug 1, 2026, the average yearly pay for machine learning research engineer in the United States is $106,012.00, according to ZipRecruiter salary data. Most workers in this role earn between $104,000.00 and $104,000.00 per year, depending on experience, location, and employer.

What does a machine learning research engineer do?

A machine learning research engineer develops and improves algorithms and models that enable computers to learn from data. They often work on creating new techniques, testing prototypes, and publishing findings, using tools like Python, TensorFlow, or PyTorch. Their work supports advancing AI capabilities and typically requires strong programming, statistical, and mathematical skills.

How much do ML research engineers make?

Machine Learning Research Engineers typically earn between $90,000 and $150,000 annually, with salaries increasing based on experience, education, and location. Senior roles or those with specialized skills in deep learning, NLP, or computer vision can earn over $200,000. Compensation often includes benefits such as bonuses, stock options, and professional development opportunities.

What does a Machine Learning Research Engineer do?

A Machine Learning Research Engineer develops and improves machine learning models, conducts research to advance AI techniques, and implements scalable algorithms. They work at the intersection of applied research and engineering, leveraging mathematical and statistical methods to optimize performance. Their role involves experimenting with new architectures, analyzing large datasets, and collaborating with data scientists and software engineers to deploy models into production.

What are some common challenges faced by Machine Learning Research Engineers in their daily work?

Machine Learning Research Engineers often encounter challenges such as sourcing and preparing large, high-quality datasets, tuning complex model architectures, and ensuring reproducibility of experimental results. They work closely with cross-functional teams, including data scientists and software engineers, to deploy models in production environments and must frequently adapt to rapidly evolving research. Keeping up with the latest scientific literature and integrating new algorithms into ongoing projects can be demanding but is also rewarding. This collaborative, fast-paced environment provides constant opportunities for learning and professional development.

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

A Machine Learning Research Engineer typically needs a strong background in computer science, mathematics, and statistics, often with a graduate degree in a related field. Proficiency in programming languages such as Python or C++, experience with machine learning frameworks like TensorFlow or PyTorch, and familiarity with tools for data analysis are crucial, along with relevant certifications being a plus. Strong problem-solving skills, collaboration, and effective communication help drive innovative research and facilitate teamwork. These competencies are essential for developing advanced machine learning models, staying current with evolving technologies, and effectively translating research into real-world applications.

What engineers make $500,000?

Senior machine learning research engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-demand industries or companies can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially in tech giants or startups with significant funding.

What engineers make $300,000 a year?

Senior machine learning research engineers with extensive experience, advanced skills in deep learning and data science, and often a strong publication record can earn $300,000 or more annually. Compensation varies based on industry, location, company size, and individual expertise, with roles in tech giants and finance firms typically offering higher salaries.
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What job categories do people searching Machine Learning Research Engineer jobs look for? The top searched job categories for Machine Learning Research Engineer jobs are:
Machine Learning Research Engineer jobs near you
Infographic showing various Machine Learning Research Engineer job openings in the United States as of July 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $106,012 per year, or $51 per hour.

Machine Learning Research Engineer

Optiver

New York, NY

$224K/yr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 18 days ago

Job description

Optiver is a seeking a Machine Learning Research Engineer to join our team, focusing on a pivotal AI initiative.  This role would offer the opportunity to have significant impact across Machine Learning infrastructure, training, and inference challenges to advance our futures trading strategies.

What you'll do

As a Machine Learning Research Engineer, your key responsibilities include:

  • Conducting innovative research on deep learning for price forecasting 
  • Building scalable and robust training and inference pipelines for deep learning
  • Diving into internals of open-source deep learning frameworks and enhance their functionality
  • Collaborating closely with researchers and other engineers
  • Developing an in-depth understanding of trading systems

What you'll get

You'll join a culture of collaboration and excellence, surrounded by curious thinkers and creative problem-solvers. Motivated by a passion for continuous improvement, you'll thrive in a supportive, high-performing environment alongside talented colleagues, collectively tackling some of the toughest challenges in the financial markets.

In addition, you'll receive:

  • The opportunity to work alongside best-in-class professionals from over 40 different countries
  • A highly competitive compensation package
  • Global profit-sharing pool and performance-based bonus structure
  • 401(k) match up to 50%
  • Comprehensive health, mental, dental, vision, disability, and life coverage
  • 25 paid vacation days alongside market holidays
  • Extensive office perks, including breakfast, lunch and snacks, regular social events, clubs, sporting leagues and more

Who you are

  • PhD or equivalent industry experience in a field related to machine learning
  • Expertise in building deep-learning models in PyTorch, JAX, or TensorFlow
  • Experience in programming in Python
  • Experience in computationally intensive research on very large data sets

Nice to have

  • Experience with JAX ecosystem (XLA, Flax, etc.)
  • Experience in programming for GPUs or other accelerators (CUDA, Triton, Pallas, etc.)
  • Contributions to open-source projects related to data science and machine learning
  • Strong publication record at conferences like NeurIPS, ICML, etc.
  • Expertise in internals of deep-learning frameworks like PyTorch, JAX, TensorFlow, etc.
  • Experience with large-scale distributed training
  • Experience in programming in C++

Who we are

At Optiver, our mission is to improve the market by injecting liquidity, providing accurate pricing, increasing transparency and stabilizing the market no matter the conditions. With a focus on continuous improvement, we prioritize safeguarding the health and efficiency of the markets for all participants. As one of the largest market making institutions, we are a respected partner on 100+ exchanges across the globe.

Our differences are our edge. Optiver does not discriminate on the basis of race, religion, color, sex, gender identity, sexual orientation, age, physical or mental disability, or other legally protected characteristics.

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