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Reinforcement Learning Engineer Jobs in Commack, NY

ML Infrastructure Engineer, Fauna

New York, NY · On-site

$117K - $154K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

You'll bring deep expertise in reinforcement learning, computer vision, and supervised learning ... programming language experience - 5+ years of leading design or architecture (design patterns ...

Founding Engineer

New York, NY · On-site

$150K - $220K/yr

Build evaluation and training loops that improve the system from simulation runs, test data, engineer corrections, and field outcomes, including reinforcement learning grounded in real physics. * Sit ...

Founding Engineer

New York, NY · Remote

$150K - $220K/yr

Build evaluation and training loops that improve the system from simulation runs, test data, engineer corrections, and field outcomes, including reinforcement learning grounded in real physics. * Sit ...

AI Engineer

New York, NY · On-site

  • Medical

  • Retirement

  • PTO

Role As an AI Engineer focused on CreditAI, our flagship GenAI product, you will own complex ... Apply reinforcement learning techniques (e.g., RLHF, RLAIF) to improve model alignment and task ...

As an AI Engineer focused on CreditAI, our flagship GenAI product, you will own complex technical ... Apply reinforcement learning techniques (e.g., RLHF, RLAIF) to improve model alignment and task ...

Showing results 21-40

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 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 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 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:

Software Development Engineer, Sponsored Products Autonomous Campaigns

Amazon

New York, NY • On-site

Full-time

Posted 10 days ago


Amazon rating

7.4

Company rating: 7.4 out of 10

Based on 7,091 frontline employees who took The Breakroom Quiz

6th of 39 rated national retailers


Job description

Build the agent execution engine powering autonomous advertising campaigns for 1.6 million advertisers - designing core infrastructure for LLM reasoning, multi-step orchestration, and reinforcement learning that enables agents to plan, reason, and act across complex advertiser workflows. Your contributions will form the backbone of the systems delivering personalized, context-aware guidance at massive scale.
The Autonomous Campaigns team within Sponsored Products and Brands is building a highly personalized campaign creation and management system that leverages LLMs together with auction simulations, ML models, and optimization algorithms. This agentic framework operates across both chat and non-chat experiences in the ad console - scaling from natural language queries to proactive guidance based on deep understanding of each advertiser

At our scale, even small improvements in guidance systems have outsized impact on advertiser success and Amazon's retail ecosystem. You'll work closely with senior engineers and applied scientists to translate research prototypes into robust, high-performance production systems - diving deep into LLM deployment frameworks, reinforcement learning infrastructure, and state-of-the-art agent architectures to solve real customer problems.
Key job responsibilities
- Implement core services and APIs for agent orchestration, tool invocation, and state management
- Build scalable, reusable data and tool registry systems that enable agents to reason across complex workflows
- Build components of evaluation pipelines (offline/online) for measuring reasoning quality, advertiser outcomes, and safety guardrails
- Develop infrastructure to support fine-tuning and reinforcement learning pipelines, collaborating with scientists to productionize workflows
- Ensure performance, scalability, observability, and maintainability through strong engineering practices
- Participate in system design, code reviews, and team architecture discussions
- Continuously learn and apply new techniques in agentic frameworks, distributed systems, and cloud-native development
About the team
The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through the latest generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights.
We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace

If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising.


What Amazon employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Amazon logo

About Amazon

Sourced by ZipRecruiter

Amazon.com, Inc., commonly known as Amazon, is an American multinational technology company. It was founded by Jeff Bezos in 1994 and initially started as an online marketplace for books. Since then, Amazon has expanded its operations and become one of the largest e-commerce companies in the world. Amazon's primary business is its online retail platform, where customers can purchase a vast array of products, including electronics, clothing, books, home goods, and much more. The company offers a convenient and user-friendly shopping experience, with features such as fast shipping, customer reviews, and personalized recommendations. In addition to its e-commerce platform, Amazon has diversified its business into various other areas. One of its notable ventures is Amazon Web Services (AWS), a comprehensive cloud computing platform that provides services such as storage, compute power, and database management to individuals and businesses. AWS has become a leader in the cloud computing industry, powering many websites and applications worldwide. Amazon has also developed its own consumer electronics, including the popular Amazon Kindle e-reader, Fire tablets, Fire TV streaming devices, and the Alexa-powered Echo smart speakers. The Alexa voice assistant, integrated into these devices, allows users to interact with their devices using voice commands, perform tasks, and access information. Furthermore, Amazon has expanded into media and entertainment. It operates Prime Video, a streaming service that offers a wide range of movies, TV shows, and original content. Amazon Music provides a platform for streaming and purchasing digital music, while Audible offers audiobooks and other audio content. The company's commitment to customer satisfaction and convenience is demonstrated by its membership program, Amazon Prime. Prime members receive various benefits, including free two-day shipping, access to streaming services, exclusive deals, and more.

Industry

It services, book publishers, retail, real estate and computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Seattle, WA, US