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Deep Reinforcement Learning Jobs (NOW HIRING)

$20/hr

Conduct research on multi-agent deep reinforcement learning, including designing novel algorithms and architectures, conducting computational experiments in benchmark environments, and compiling ...

Deep Learning NLP 3 * Python & pytorch * PyTorch * GPU LLM Trouble shooting * Slurm, DDP, Horovod Preferred Qualifications * Deep Learning/NLP (ACL, EMNLP, NeurIPS) * Docker Kubernetes * GPU * GPU ...

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Deep Reinforcement Learning information

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$28.5K

$58.3K

$80K

How much do deep reinforcement learning jobs pay per year?

As of May 28, 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 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.

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 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:
Infographic showing various Deep Reinforcement Learning job openings in the United States as of May 2026, with employment types broken down into 88% Full Time, 10% Part Time, and 2% Contract. Highlights an 18% Physical, and 82% Remote job distribution, with an average salary of $58,347 per year, or $28.1 per hour.

Senior Machine Learning Engineer - Deep & Reinforcement Learning

Kanak Elite Services Inc

Houston, TX • On-site

$99.80K - $137K/yr

Contractor

Posted 11 days ago


Job description

Hello There,

My name is Himanshu Sharma, and I serve as the Recruitment Lead at Kanak-IT INC. I am reaching out to share an excellent career opportunity for the role of Senior Machine Learning Engineer with our esteemed client. If you are interested then please share your updated resume at Himanshu01@kanakits.com .

Job Description

Position           : Senior Machine Learning Engineer – Deep & Reinforcement Learning

Location          : Houston, TX Onsite

Duration         : Long term contract

Required skills:
- Degree in STEM field, Ph.D preferred.
- Master in Deep Learning, Reinforcement Learning, and multimodal large language model.
- Strong Pytorch or TensorFlow programming
- Machine Learning and Statistical Modelling - Mastery
- Exploratory Analysis
- Core Programming Skills & Languages
- AI Engineering Essentials
- DevOps and Agile
- Cloud deployment frameworks, infrastructure, and tooling