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Reinforcement Learning Engineer Jobs in New Jersey

Amazon

Applied Scientist

Newark, NJ · On-site

... Engineering, Data Science, Applied Math, or a related quantitative field - 3+ years of experience in Deep Learning, Natural Language - Processing/Understanding, GenAI and/or Reinforcement Learning ...

J.P. Morgan

Lead Software Engineer

Jersey City, NJ · On-site

On this team you will work with cutting-edge techniques in disciplines such as Deep Learning and Reinforcement Learning. As a Lead Software Engineer at JPMorgan Chase within the Corporate Sector ...

Tata Consultancy Services

AI Researcher

Edison, NJ · On-site

From visual perception and SLAM to multimodal sensor fusion and reinforcement learning, you'll be ... Partner with cross-functional teams in AI, robotics, and systems engineering to co-create ...

Tata Consultancy Services

AI Researcher

Edison, NJ

From visual perception and SLAM to multimodal sensor fusion and reinforcement learning, you'll be ... Partner with cross-functional teams in AI, robotics, and systems engineering to co-create ...

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Showing results 21-40

All JobsReinforcement Learning Engineer JobsReinforcement Learning Engineer Jobs in New Jersey

Reinforcement Learning Engineer information

See New Jersey salary details

$38.6K

$117.6K

$194.4K

How much do reinforcement learning engineer jobs pay per year?

As of Sep 6, 2026, the average yearly pay for reinforcement learning engineer in New Jersey is $117,630.00, according to ZipRecruiter salary data. Most workers in this role earn between $84,300.00 and $153,800.00 per year, depending on experience, location, and employer.

What is a reinforcement learning engineer?

Reinforcement Learning Engineers are specialized professionals who design, develop, and implement algorithms based on reinforcement learning, a type of machine learning where agents learn to make decisions by receiving rewards or penalties. They work on building models that enable machines to learn optimal actions through trial and error in complex environments. Their responsibilities often include developing RL architectures, tuning hyperparameters, running simulations, and applying RL methods to real-world problems like robotics, gaming, or recommendation systems. RL Engineers typically have strong backgrounds in computer science, mathematics, and deep learning, along with experience in programming languages like Python and frameworks such as TensorFlow or PyTorch.

What are some common challenges faced by reinforcement learning engineers when deploying models in real-world environments?

One of the main challenges Reinforcement Learning (RL) Engineers face is bridging the gap between simulation and real-world deployment. Models that perform well in controlled environments may struggle with unpredictable data, safety constraints, or limited feedback in production. Additionally, RL algorithms often require significant computational resources and careful tuning to avoid instability. Collaboration with domain experts and software engineers is essential to address these issues and ensure successful integration of RL solutions into existing systems.

What are the key skills and qualifications needed to thrive as a reinforcement learning engineer, and why are they important?

To thrive as a Reinforcement Learning Engineer, you need a strong background in machine learning, mathematics (especially probability and statistics), and programming languages like Python, often supported by a relevant degree in computer science or engineering. Familiarity with deep learning frameworks (such as TensorFlow or PyTorch), RL libraries (like OpenAI Gym), and cloud computing platforms is typically required. Problem-solving skills, creativity, and effective collaboration help set outstanding engineers apart in this field. These competencies enable the design and deployment of advanced RL solutions that address real-world challenges and drive innovation.

What is the difference between Reinforcement Learning Engineer vs Machine Learning Engineer?

AspectReinforcement Learning EngineerMachine Learning Engineer
CredentialsBachelor's/Master's in CS, AI, or related; experience with RL frameworksBachelor's/Master's in CS, Data Science, or related; experience with ML algorithms
Work EnvironmentResearch labs, AI startups, tech companies focusing on RL applicationsTech companies, data-driven firms, AI departments across industries
Industry UsageSpecialized in RL projects like robotics, game AI, autonomous systemsBroader applications including predictive modeling, NLP, computer vision

Reinforcement Learning Engineers focus on developing algorithms that learn through interactions with environments, often in robotics or gaming. Machine Learning Engineers work on a wider range of models and applications. While both roles require strong programming and math skills, RL Engineers specialize in sequential decision-making, whereas ML Engineers handle diverse data-driven tasks across industries.

What are popular job titles related to Reinforcement Learning Engineer jobs in New Jersey?

For Reinforcement Learning Engineer jobs in New Jersey, the most frequently searched job titles are:

What job categories do people searching Reinforcement Learning Engineer jobs in New Jersey look for?

The top searched job categories for Reinforcement Learning Engineer jobs in New Jersey are:

What cities in New Jersey are hiring for Reinforcement Learning Engineer jobs?

Cities in New Jersey with the most Reinforcement Learning Engineer job openings:

Reinforcement Learning Engineer jobs near you
Infographic showing various Reinforcement Learning Engineer job openings in New Jersey as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 21% Part Time, 2% Temporary, and 2% Contract. Highlights an 83% Physical, 3% Hybrid, and 14% Remote job distribution, with an average salary of $117,630 per year, or $56.6 per hour.

Software Engineer III - Agentic AI, Java/Python

JPMorganChase

Jersey City, NJ • On-site

Full-time

Re-posted 23 days ago

Job description

Job Summary:
JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers and businesses. They are seeking a Software Engineer III to design and deliver AI/ML technology products, executing solutions and developing high-quality production code to support the firm's business objectives.
Responsibilities:
• Deliver AI/ML projects through our ML development life cycle using Agile methodology. Help transform business requirements into AI/ML specifications, define milestones, and ensure timely delivery.
• Executes solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
• Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems
• Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development
• Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems
• Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture
• Contributes to software engineering communities of practice and events that explore new and emerging technologies
Qualifications:
Required:
• Formal training or certification on software engineering concepts and 3+ years applied experience
• Experience as a hands-on practitioner developing production AI/ML solutions.
• Familiarity with agentic workflows and relevant frameworks, such as LangChain, LangGraph, Auto-GPT etc.
• Deep knowledge and experience in machine learning and artificial intelligence.
• Expert in at least one of the following areas: Large Language Models, Natural Language Processing, Knowledge Graph, Computer Vision, Speech Recognition, Reinforcement Learning, Ranking and Recommendation, or Time Series Analysis.
• Knowledge of Data structures, Algorithms, Machine Learning, Data Mining, Information Retrieval, Statistics.
• Demonstrated understanding in machine learning frameworks: Tensorflow, Pytorch, pyG, Keras, MXNet, Scikit-Learn.
• Strong programming knowledge of python, spark; Strong grasp on vector operations using numpy, scipy; Strong grasp on distributed computation using Multithreading, Multi GPUs, Dask, Ray, Polars etc.
• Familiarity in AWS Cloud services such as EMR, Sagemaker etc.
• Overall knowledge of the Software Development Life Cycle
• Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
Preferred:
• Exposure to cloud technologies
Company:
With a history tracing its roots to 1799 in New York City, JPMorganChase is one of the world's oldest, largest, and best-known financial institutions—carrying forth the innovative spirit of our heritage firms in global operations across 100 markets. Founded in 2000, the company is headquartered in New York, USA, with a team of 10001+ employees. The company is currently Late Stage.

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