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Reinforcement Learning Engineer Jobs in Commack, NY

EDEN is a digital design environment for engineering and designing ecosystems, modeling the flows ... Develop and refine advanced deep generative models and reinforcement learning algorithms for built ...

Senior AI Engineer

New York, NY · On-site

$95K - $300K/yr

Senior AI Engineer New York City | Hybrid Onsite | Full Time Mission Let's make high-quality health ... Models and Learning * Apply methods such as fine-tuning, distillation, reinforcement learning ...

RESEARCH SCHOLAR

New York, NY · On-site

$27/hr

Hao Su ( at NYU Tandon School of Engineering is seeking to hire a Part Time Research Scholar (Non-PhD) to work on mechatronics design, control, and reinforcement learning for wearable robots ...

... feature engineering and deep learning architecture design to training dynamics and execution ... Reinforcement learning experience is a bonus * Results oriented mindset with a focus on developing ...

Machine Learning Researcher

New York, NY · On-site

$200K - $300K/yr

... feature engineering and deep learning architecture design to training dynamics and execution ... Reinforcement learning experience is a bonus * Results oriented mindset with a focus on developing ...

... engineering and product leaders with decades of experience. The Role: We are looking for PhD research interns with strong research experience in reinforcement learning, machine learning, and ...

Research Engineer

New York, NY · On-site

$200K - $400K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

We're looking for a Research Engineer to build the intelligent systems that power Antimetal. You'll ... reinforcement learning. Evaluation: Making sure agents work well and informing how we improve.

Founding Research Engineer

New York, NY · On-site

$215K - $330K/yr

  • Medical

  • PTO

We use those environments to improve model performance through reinforcement learning and other post-training techniques, alongside context engineering, harness design, and agent engineering. The ...

Senior AI Scientist (m/f/d) working directly on engineering advanced AI systems and world model's reasoning algorithms * Develop simulation environments and reinforcement learning, planning and ...

Software Engineer - Training Product

New York, NY · On-site

$165K - $330K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

You'll own features like multi-node training and products like serverless reinforcement learning ... You'll work closely with research engineers leveraging state-of-the-art training techniques to ...

Showing results 41-60

Reinforcement Learning Engineer information

See Commack, NY salary details

$39.4K

$120K

$198.3K

How much do reinforcement learning engineer jobs pay per year?

As of Aug 16, 2026, the average yearly pay for reinforcement learning engineer in Commack, NY is $119,983.00, according to ZipRecruiter salary data. Most workers in this role earn between $86,000.00 and $156,900.00 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 Commack, NY?

For Reinforcement Learning Engineer jobs in Commack, NY, the most frequently searched job titles are:

What cities near Commack, NY are hiring for Reinforcement Learning Engineer jobs?

Cities near Commack, NY with the most Reinforcement Learning Engineer job openings:

Applied AIML & Gen AI Executive Director - Machine Learning Center of Excellence

J.P. Morgan

New York, NY

Full-time

Medical, Retirement

Re-posted 10 days ago


Job description

hackajob is collaborating with J.P. Morgan to connect them with exceptional professionals for this role.

JOB DESCRIPTION

The Chief Data & Analytics Office (CDAO) at JPMorgan Chase is responsible for accelerating the firm’s data and analytics journey. This includes ensuring the quality, integrity, and security of the company's data, as well as leveraging this data to generate insights and drive decision-making. The CDAO is also responsible for developing and implementing solutions that support the firm’s commercial goals by harnessing artificial intelligence and machine learning technologies to develop new products, improve productivity, and enhance risk management effectively and responsibly.

This role offers the unique opportunity to explore novel and complex challenges that could profoundly transform how the bank operates. 

As a Machine Learning Director, you will have the opportunity to apply sophisticated machine learning methods to complex tasks including natural language processing, speech analytics, time series, reinforcement learning and recommendation systems. You will collaborate with various teams and actively participate in our knowledge sharing community. We are looking for someone who excels in a highly collaborative environment, working together with our business, technologists and control partners to deploy solutions into production. If you have a strong passion for machine learning and enjoy investing time towards learning, researching and experimenting with new innovations in the field, this role is for you. We value solid expertise in Deep Learning with hands-on implementation experience, strong analytical thinking, a deep desire to learn and high motivation.

Job Responsibilities

  • Research and explore new machine learning methods through independent study, attending industry-leading conferences, experimentation and participating in our knowledge sharing community
  • Develop state-of-the art machine learning models to solve real-world problems and apply it to tasks such as natural language processing (NLP), speech recognition and analytics, time-series predictions or recommendation systems
  • Collaborate with multiple partner teams such as Business, Technology, Product Management, Legal, Compliance, Strategy and Business Management to deploy solutions into production
  • Drive Firm wide initiatives by developing large-scale frameworks to accelerate the application of machine learning models across different areas of the business
     

Required qualifications, capabilities, and skills

  • PhD in a quantitative discipline, e.g. Computer Science, Electrical Engineering, Mathematics, Operations Research, Optimization, or Data Science Or an MS with at least 7 years of industry or research experience in the field.
  • Solid background in NLP or speech recognition and analytics, personalization/recommendation and hands-on experience and solid understanding of machine learning and deep learning methods
  • Extensive experience with machine learning and deep learning toolkits  (e.g.: TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas)
  • Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals
  • Experience with big data and scalable model training and solid written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences.
  • Scientific thinking with the ability to invent and to work both independently and in highly collaborative team environments
  • Solid written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences. Curious, hardworking and detail-oriented, and motivated by complex analytical problems

Preferred qualifications, capabilities , and skills:

  • Strong background in Mathematics and Statistics and familiarity with the financial services industries and continuous integration models and unit test development
  • Knowledge in search/ranking, Reinforcement Learning or Meta Learning
  • Experience with A/B experimentation and data/metric-driven product development, cloud-native deployment in a large scale distributed environment and ability to develop and debug production-quality code
  • Published research in areas of Machine Learning, Deep Learning or Reinforcement Learning at a major conference or journal

#MLCOE_jobs

ABOUT US
JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process. 

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.

JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans

ABOUT THE TEAM
Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we’re setting our businesses, clients, customers and employees up for success.