ZipRecruiter

Log In

1

Deep Reinforcement Learning Jobs (NOW HIRING)

Apptronik

Senior Reinforcement Learning Engineer

Austin, TX · On-site

$103K - $142K/yr

JOB SUMMARY The Senior Reinforcement Learning Engineer is a key, hands-on role focused on achieving ... This engineer will leverage their deep expertise in RL to solve critical locomotion and ...

Bostondynamics

Staff, ML Research Scientist

Waltham, MA · On-site

$154K - $192K/yr

Experience in the full modeling cycle from research to deployment of modern Deep Learning architectures such as Transformers, VLMs/VLAs, and Deep Reinforcement Learning. * Knowledge of ...

MLabs

Reinforcement Learning Engineer

New York, NY · On-site

$87K - $118K/yr

Reinforcement Learning (RL) Engineer Location: New York (Office) On-site | Full-time Compensation ... A deep-dive assessment into RL architecture, simulation frameworks, and live production experience.

MLabs

Reinforcement Learning Engineer

New York, NY · On-site

$87K - $118K/yr

Reinforcement Learning (RL) Engineer Location: New York (Office) On-site | Full-time Compensation ... A deep-dive assessment into RL architecture, simulation frameworks, and live production experience.

poolside

Member of Engineering (Reinforcement Learning)

$99K - $136K/yr

What unites us is our deep care for what we build together. We're in a race that requires hard work ... ABOUT THE ROLE You would be working on our reinforcement learning team focused on improving ...

MLabs

Reinforcement Learning Engineer

New York, NY · On-site

$87K - $118K/yr

Reinforcement Learning (RL) Engineer Location: New York (Office) On-site Full-time Compensation ... A deep-dive assessment into RL architecture, simulation frameworks, and live production experience.

next page

Showing results 1-20

All JobsDeep Reinforcement Learning Jobs

Deep Reinforcement Learning information

See salary details

$28.5K

$58.3K

$80K

How much do deep reinforcement learning jobs pay per year?

As of Jul 8, 2026, the average yearly pay for deep reinforcement learning in the United States is $58,347.00, according to ZipRecruiter salary data. Most workers in this role earn between $50,500.00 and $68,000.00 per year, depending on experience, location, and employer.

What does a typical day look like for someone working in Deep Reinforcement Learning?

A typical day for a Deep Reinforcement Learning professional involves designing algorithms, running experiments, analyzing results, and optimizing models to improve performance. You may collaborate regularly with data scientists, software engineers, and domain experts to integrate RL solutions into larger systems or products. Tasks often include reading the latest research, contributing to code reviews, and documenting findings while troubleshooting technical challenges. This dynamic environment encourages continuous learning and teamwork, ensuring you stay at the forefront of AI innovation.

What is a Deep Reinforcement Learning job?

A Deep Reinforcement Learning (DRL) job involves researching, developing, and applying AI models that use reinforcement learning techniques combined with deep learning. Professionals in this role design algorithms that enable agents to learn optimal decision-making policies through trial and error. Common applications include robotics, game AI, autonomous systems, and financial modeling. This job typically requires expertise in machine learning, neural networks, and programming languages like Python, along with frameworks such as TensorFlow or PyTorch.

What are the key skills and qualifications needed to thrive in the Deep Reinforcement Learning position, and why are they important?

To thrive in Deep Reinforcement Learning, you need expertise in machine learning, programming (Python, TensorFlow, or PyTorch), and applied mathematics, often supported by an advanced degree in computer science or a related field. Familiarity with version control systems, cloud computing platforms, and relevant certifications in AI or data science are valuable assets. Strong problem-solving abilities, collaboration, and effective communication are important soft skills in this position. These skills are essential for developing, implementing, and iterating cutting-edge algorithms that solve complex real-world problems in dynamic environments.

More about Deep Reinforcement Learning jobs
What are the most commonly searched types of Deep Reinforcement Learning jobs? The most popular types of Deep Reinforcement Learning jobs are:
What states have the most Deep Reinforcement Learning jobs? States with the most job openings for Deep Reinforcement Learning jobs include:
What job categories do people searching Deep Reinforcement Learning jobs look for? The top searched job categories for Deep Reinforcement Learning jobs are:
Deep Reinforcement Learning jobs near you
Infographic showing various Deep Reinforcement Learning job openings in the United States as of July 2026, with employment types broken down into 17% Internship, 49% Full Time, 17% Part Time, and 17% Contract. Highlights an 83% In-person, and 17% Remote job distribution, with an average salary of $58,347 per year, or $28.1 per hour.

Machine Learning Scientist, Reinforcement Learning

Profluent

Emeryville, CA • On-site, Remote

$200K - $330K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 4 days ago

Job description

Profluent is an AI-first protein design company. Founded in 2022, we develop deep generative models to design and validate novel, functional proteins to revolutionize biomedicine. Based in Emeryville, CA, we are backed by leading investors including Altimeter Capital, Bezos Expeditions, Spark Capital, Insight Partners, Air Street Capital, AIX Ventures, and Convergent Ventures, and have raised over $150M to date.
We're looking for a motivated and creative Machine Learning (ML) Scientist to drive research into reinforcement learning for biomolecular design. This position offers an opportunity to work at the forefront of generative modeling research across language processing, representation learning, and protein engineering. You should be a self-directed researcher who has the ability to rapidly prototype and evaluate new models and algorithms in the biomolecular domain.
As an early employee, you will proactively shape the direction of our machine learning efforts and collaborate across diverse teams of computational and experimental scientists.
Responsibilities
  • Design and develop state-of-the-art online and offline reinforcement learning algorithms for protein design
  • Collaborate across the machine learning and protein design teams to adapt and improve reinforcement learning techniques from other domains to protein design
  • Architect, implement, and optimize core infrastructure to support the post-training of protein language models
  • Curate relevant datasets and design tasks for rigorous evaluation of generative models
  • Implement, analyze, and interpret multiple computational approaches and present results to colleagues in regular update meetings
  • Work within a collaborative, fast-paced, interdisciplinary team across biology and machine learning to help shape the scientific and strategic vision of the company

Qualifications
  • PhD (or equivalent industry experience) in Computer Science, Machine Learning, Natural Language Processing, Applied Math, Computational Biology, Statistics, or a related field
  • Experience with conceiving of, implementing, and evaluating novel machine learning and reinforcement learning techniques
  • Publications at major machine learning conferences (NeurIPS, ICML, ICLR) or scientific journals (Nature, Science, Nature Biotech, Nature Methods, PNAS)
  • Experience with modern deep learning frameworks such as Pytorch or Jax

Preferences (but not required)
  • Familiarity with foundational biology of proteins and nucleic acids
  • Experience developing machine learning models for proteins (language models, structure prediction, design)
  • Experience with cloud compute platforms (GCP, AWS, Azure, OCI)
  • Previous experience in data extraction and curation from bioinformatics data sources
  • Familiarity with wet lab experimental assays and associated limitations

What We Offer
  • High-growth opportunity with meaningful impact on the future of protein design
  • Competitive compensation package with equity participation
  • 401(k) with a strong employer match
  • Comprehensive benefits including health/dental/vision insurance
  • Generous PTO policy and commitment to work-life balance
  • Professional development opportunities in a cutting-edge field at the intersection of AI and biology

Profluent Bio, Inc is an equal opportunity employer promoting diversity and inclusion in the workspace. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical conditions, veteran status, sexual orientation, gender (including gender identity and gender expression), sex (which includes pregnancy, childbirth, and breastfeeding), genetic information, taking or requesting statutorily protected leave, or any other basis protected by law.
Employment Eligibility Verification
Legal authorization to work in the United States is required. In compliance with federal law, all persons hired must verify their identity and work eligibility and complete the required employment verification form upon hire.
Hiring Salary Range
$200,000-$330,000 USD

Apply