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Deep Learning Researcher Jobs (NOW HIRING)

Matroid

Deep Learning Engineer

Palo Alto, CA · On-site

$170K - $300K/yr

Keep on top of the latest developments and research in academic CV/DL and decide how we should ... Passion for computer vision and deep learning; you are excited to adapt the latest multimodal LLMs ...

Jane Street

Machine Learning Researcher

New York, NY · On-site

... Learning Researcher while also providing a truly unparalleled educational experience. You'll work ... Depending on the day, you might be diving deep into market data, tuning hyperparameters, debugging ...

Jane Street

Machine Learning Researcher

New York, NY · On-site

On our Machine Learning team, you'll build the deep learning models that power our trading ... At Jane Street, our researchers, engineers, and traders sit a few feet away from each other and ...

Jane Street

Machine Learning Researcher

New York, NY · On-site

On our Machine Learning team, you'll build the deep learning models that power our trading ... At Jane Street, our researchers, engineers, and traders sit a few feet away from each other and ...

IMC

Machine Learning Researcher

Chicago, IL · On-site

$250K - $300K/yr

... learning to solve challenging trading problems. This role is part of a central ML research team ... This is an opportunity to dive deep into feature engineering and alpha research, and focus on ...

MSCI

Machine Learning Researcher

San Francisco, CA

$144K - $187K/yr

Conduct research using machine learning methodologies that integrate financial theory with deep learning and reinforcement learning * Design and develop models that convert AI-extracted signals from ...

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All JobsDeep Learning Researcher Jobs

Deep Learning Researcher information

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$30K

$113.1K

$164.5K

How much do deep learning researcher jobs pay per year?

As of Jul 17, 2026, the average yearly pay for deep learning researcher in the United States is $113,102.00, according to ZipRecruiter salary data. Most workers in this role earn between $67,000.00 and $154,000.00 per year, depending on experience, location, and employer.

What are some common challenges faced by Deep Learning Researchers when transitioning models from research to production environments?

Deep Learning Researchers often encounter challenges such as ensuring model robustness, addressing scalability issues, and optimizing computational efficiency when moving models from research to production. Real-world data can be noisier or more variable than research datasets, requiring additional data preprocessing and validation. Collaboration with engineering teams is crucial to integrate models effectively, and researchers may need to adapt their algorithms to meet latency and resource constraints of production environments.

What is a Deep Learning Researcher?

A Deep Learning Researcher is a specialist who develops and investigates advanced algorithms and models that allow computers to learn from large amounts of data, particularly using artificial neural networks. They focus on designing, training, and evaluating deep learning models to solve complex problems in areas like computer vision, natural language processing, and speech recognition. Their work often involves staying up to date with the latest advancements in machine learning and contributing to research publications. Deep Learning Researchers may work in academia, industry, or research labs, collaborating with other scientists and engineers to push the field forward.

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

To thrive as a Deep Learning Researcher, you need a strong background in computer science, mathematics, and machine learning principles, typically supported by an advanced degree (Master’s or PhD) in a related field. Proficiency with frameworks like TensorFlow or PyTorch, experience with high-performance computing, and familiarity with relevant programming languages such as Python are essential. Strong problem-solving, collaboration, and communication skills help you innovate and effectively share research findings. These skills and qualities are crucial for advancing state-of-the-art models and driving impactful AI solutions.

What is the difference between Deep Learning Researcher vs Machine Learning Engineer?

AspectDeep Learning ResearcherMachine Learning Engineer
CredentialsAdvanced degrees in AI, CS, or related fields; research publicationsDegree in CS, Data Science, or related; practical experience
Work EnvironmentResearch labs, academia, R&D departmentsIndustry, product teams, deployment environments
Employer & Industry UsageUniversities, research institutes, tech companiesTech companies, startups, enterprise firms
Primary FocusDeveloping new algorithms, theoretical advancementsImplementing models, deploying solutions, optimizing systems

While both roles involve working with machine learning models, Deep Learning Researchers focus on advancing the theoretical foundations and developing new algorithms, often in research settings. Machine Learning Engineers apply these models in real-world applications, focusing on deployment and system optimization.

More about Deep Learning Researcher jobs
What job categories do people searching Deep Learning Researcher jobs look for? The top searched job categories for Deep Learning Researcher jobs are:
Deep Learning Researcher jobs near you
Infographic showing various Deep Learning Researcher job openings in the United States as of July 2026, with employment types broken down into 73% Full Time, 25% Part Time, and 2% Contract. Highlights an 72% Physical, 2% Hybrid, and 26% Remote job distribution, with an average salary of $113,102 per year, or $54.4 per hour.
Deep Learning Engineer

Deep Learning Engineer

Matroid

Palo Alto, CA • On-site

$170K - $300K/yr

Full-time

Medical, Dental, Vision

Re-posted 4 days ago

Job description

About Matroid

Matroid is a full-service computer vision company that has developed an end-to-end platform allowing enterprise customers to rapidly train and
deploy automated visual inspection on imagery including EO, IR, X-Ray, CT, OCT, and others.

Founded in 2016 by a Stanford professor, Matroid has a broad and rapidly growing set of customers in manufacturing, industrial IoT, government and security.

We are looking for a world-class Deep Learning Software Engineer who is excited to operate at the forefront of computer vision and deep learning applied to challenging, real-world use-cases. You will be working in a fast-paced environment, surrounded by experts who are passionate about their work.

This position is onsite at our downtown Palo Alto office, located near the Stanford campus and Caltrain.

What you'll do

  • Advance the computer vision and deep learning technology powering Matroid's computer vision platform
  • Keep on top of the latest developments and research in academic CV/DL and decide how we should apply them to our real world use-cases
  • Engineer new DL capabilities end-to-end; research, experiment, iterate, develop, optimize and productionize

How you'll be doing it

  • Operating in a collaborative but highly autonomous environment where you are empowered to make an impact
  • Knowing that everything you build affects real-world users, with corresponding quality standards for your work
  • Collaborating with other DL engineers, as well as our other expert teams, including product, infrastructure, and field engineering

What you bring to the table

  • Masters in Computer Science, Software Engineering, Mathematics, or equivalent
  • Passion for computer vision and deep learning; you are excited to adapt the latest multimodal LLMs, or implement a video transformer model from scratch, or get realtime segmentation running on a tiny edge device, or train a massive industry-specific foundation model
  • 3+ years of industry and/or academic experience relating to software, deep learning and computer vision
  • Experience using and modifying state-of-the-art CV models and frameworks, with understanding of their theoretical underpinnings
  • Knowledge of model architectures and techniques across a broad range of domains, including object detection, segmentation, anomaly detection, object tracking, video-understanding and vision language models
  • Strong software engineering skills - you care deeply about the quality of your code
  • Solid oral, written, presentation, collaboration, and interpersonal communication skills

Bonus points if...

  • Specialization in CV, artificial intelligence, machine learning, or related fields
  • Significant computer vision & deep learning academic and/or research experience
  • Prior work experience with applied computer vision in real-world use-cases
  • Cool personal projects, competitions, hackathons, etc. demonstrating your passion & expertise
  • Previous work at high-growth technology startups

What we offer in return

  • Competitive pay and equity.
  • The chance to constantly work on stimulating intellectual challenges.
  • Gym membership reimbursement.
  • Free lunch, healthy drinks, and snacks every day.
  • Medical, dental, and vision insurance with 100% paid premiums.
  • A flexible schedule that leaves time for all of your other interests.
  • A budget for whatever hardware or software will make you most effective.
  • Regular tech talks to discuss the latest advances in CV, DL and engineering

Matroid is committed to creating a diverse work environment and is proud to be an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, sex, gender identity, sexual orientation, age, non-disqualifying physical or mental disability, national origin, veteran status, or any other basis covered by appropriate law.