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Openai Reinforcement Learning Jobs (NOW HIRING)

IT360, Inc.

AI Engineer

Peoria, IL · On-site

$75K - $110K/yr

Retrieval-Augmented Generation (RAG), AI scoring (Model Performance Metrics), reinforcement learning * LLM Platforms: OpenAI, Claude, Gemini * Microsoft 365 Stack: CoPilot, Power Automate, Function ...

JazzX AI

Senior Staff AI Engineer

Los Altos, CA · On-site

$65.50 - $84.50/hr

Deep expertise in reinforcement learning algorithms , including on-policy (PPO, A3C) and off-policy (SAC, DDPG) methods, along with hands-on work in simulation frameworks (e.g., OpenAI Gym, Isaac Gym ...

IT360 Inc

AI Engineer

Peoria, IL · On-site

Retrieval-Augmented Generation (RAG), AI scoring (Model Performance Metrics), reinforcement learning * LLM Platforms: OpenAI, Claude, Gemini * Microsoft 365 Stack: CoPilot, Power Automate, Function ...

JazzX AI

Senior Staff AI Engineer

San Francisco, CA · On-site

$65 - $84/hr

Deep expertise in reinforcement learning algorithms , including on-policy (PPO, A3C) and off-policy (SAC, DDPG) methods, along with hands-on work in simulation frameworks (e.g., OpenAI Gym, Isaac Gym ...

Granite Telecommunications

Lead AI Engineer

Quincy, MA · On-site

$180K - $280K/yr

Developing and applying reinforcement learning strategies to optimize and automate decision-making ... Develop and implement AI solutions leveraging fine-tuned Large Language Models (e.g., OpenAI models ...

Career Site

Lead AI Engineer

Quincy, MA · On-site +1

$180K - $280K/yr

Developing and applying reinforcement learning strategies to optimize and automate decision-making ... Develop and implement AI solutions leveraging fine-tuned Large Language Models (e.g., OpenAI models ...

Rogo

AI Researcher

New York, NY · On-site

Experience working directly in training or post-training LLM at a frontier lab (OpenAI, Anthropic, DeepMind, Meta) * Experience with deep reinforcement learning in any context (autonomous vehicles ...

Zillow

Principal Machine Learning Engineer, Agentic AI

$194K - $310K/yr

They'll be developing perception and language understanding, deep reasoning, and reinforcement ... from OpenAI or open source) with large-scale engineering. We are looking for someone who has: * A ...

Zillow

Principal Machine Learning Engineer, Agentic AI

OR · On-site +1

$204K - $326K/yr

They'll be developing perception and language understanding, deep reasoning, and reinforcement ... from OpenAI or open source) with large-scale engineering. We are looking for someone who has: * A ...

CCS INC

Gen AI Engineer

Plano, TX · On-site

$40 - $50/hr

Implement prompt engineering, instruction tuning, and reinforcement learning from human feedback ... OpenAI, Anthropic, etc.

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Openai Reinforcement Learning information

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$28.5K

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$80K

How much do openai reinforcement learning jobs pay per year?

As of Jun 12, 2026, the average yearly pay for openai 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.

Is ML a high paying job?

Machine Learning (ML) roles, including positions like OpenAI Reinforcement Learning engineers, are generally well-paid due to the specialized skills required, such as programming, data analysis, and knowledge of algorithms. Salaries tend to be higher than average in tech hubs and often include benefits like stock options and bonuses, reflecting the demand for expertise in AI and ML development.

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

AspectOpenai Reinforcement LearningMachine Learning Engineer
Required CredentialsKnowledge of reinforcement learning algorithms, programming skills, possibly advanced degrees in AI or CSStrong programming skills, proficiency in ML frameworks, degrees in CS, data science, or related fields
Work EnvironmentResearch labs, AI development teams, experimental projectsTech companies, startups, data-driven organizations, software development teams
Industry UsageAI research, autonomous systems, game AI, roboticsProduct development, predictive modeling, data analysis, deployment of ML models

Openai Reinforcement Learning focuses on developing algorithms that enable agents to learn through trial and error in dynamic environments, often in research settings. Machine Learning Engineers implement and optimize ML models for practical applications across various industries. While both roles require programming skills and knowledge of AI, reinforcement learning specialists concentrate on experimental algorithms, whereas ML engineers focus on deploying scalable solutions.

Is it hard to get hired at OpenAI?

Getting hired for roles related to OpenAI reinforcement learning typically requires a strong background in machine learning, deep learning, and programming skills in Python. Candidates often need relevant research experience, a solid understanding of reinforcement learning algorithms, and a track record of contributions to AI projects or publications. The hiring process is competitive and may include technical interviews and assessments.

What are the key skills and qualifications needed to thrive as an OpenAI Reinforcement Learning Engineer, and why are they important?

To excel as an OpenAI Reinforcement Learning Engineer, you need a solid background in computer science, machine learning, and mathematics, often supported by advanced degrees (MS/PhD) in related fields. Experience with deep learning frameworks like TensorFlow or PyTorch, familiarity with RL-specific libraries (such as OpenAI Gym), and strong programming skills in Python are critical. Problem-solving ability, collaboration, and clear communication distinguish outstanding candidates in this role. These competencies are vital for designing, implementing, and optimizing RL algorithms that advance state-of-the-art AI systems.

Does OpenAI do reinforcement learning?

OpenAI actively researches and applies reinforcement learning techniques to develop advanced AI models, including training agents to improve performance through trial and error. Reinforcement learning is a core component of some OpenAI projects, and expertise in this area is valuable for roles involving AI development and machine learning. Knowledge of algorithms like Q-learning and policy optimization is often required.

What is OpenAI Reinforcement Learning?

OpenAI Reinforcement Learning refers to the use of reinforcement learning (RL) techniques, often developed or researched by OpenAI, to train artificial intelligence agents. In reinforcement learning, agents learn to make decisions by interacting with an environment to maximize accumulated rewards. OpenAI has pioneered several advancements in RL, such as training agents to play games, control robots, and solve complex sequential problems. These approaches have led to breakthroughs like OpenAI Five for Dota 2 and improvements in general AI capabilities. RL at OpenAI often involves large-scale simulations, deep learning, and innovative exploration strategies.

How does an OpenAI Reinforcement Learning Engineer typically collaborate with researchers and software engineers on projects?

As an OpenAI Reinforcement Learning Engineer, you will frequently work in cross-functional teams that include research scientists, software engineers, and sometimes product managers. Collaboration often involves jointly designing experiments, sharing insights from model performance, and integrating new algorithms into production environments. Clear communication and documentation are vital, as your work may directly inform ongoing research and product development. You'll participate in regular meetings, code reviews, and brainstorming sessions to ensure alignment and drive innovation.

Which 3 jobs will survive AI?

In the field of OpenAI Reinforcement Learning, jobs such as AI research scientists, machine learning engineers, and data scientists are likely to persist as they require advanced understanding of complex algorithms, programming skills, and domain expertise. These roles involve designing, developing, and refining AI models, which are less susceptible to automation due to their specialized knowledge and problem-solving requirements.
Infographic showing various Openai Reinforcement Learning job openings in the United States as of June 2026, with employment types broken down into 9% Locum Tenens, 76% Full Time, 2% Contract, 11% Nights, and 2% Summer. Highlights an 92% Physical, 2% Hybrid, and 6% Remote job distribution, with an average salary of $58,347 per year, or $28.1 per hour.
AI Engineer

AI Engineer

IT360, Inc.

Peoria, IL • On-site

$75K - $110K/yr

Full-time

Medical, Life, Retirement, PTO

Posted 12 days ago

Job description

Job Title: AI Engineer
Location: Peoria, IL
Work Environment: IN-OFFICE ONLY (Peoria, IL) Not a remote or hybrid position.
Job Type: Full-Time
About the Role
IT360, Inc. is seeking a highly skilled and innovative AI Engineer to join our growing team. This strategic, client-facing role is responsible for designing, developing, and leading deployment of AI-driven solutions and automations that address complex business challenges for both internal operations and external clients. You'll work with a variety of machine learning, automations, and scripting technologies to deliver intelligent, secure, and scalable solutions tailored to client needs.
Key Responsibilities
  • Design and develop scalable AI/ML models to solve real-world problems across various domains.
  • Collaborate with clients to identify AI opportunities and define solution requirements.
  • Build and maintain end-to-end machine learning pipelines, from data ingestion and preprocessing to model training, evaluation, and deployment.
  • Integrate AI solutions into existing systems and platforms, ensuring performance, reliability, and scalability.
  • Monitor and improve the performance of deployed models through continuous evaluation and retraining.
  • Stay current with the latest advancements in AI/ML research and tools, and apply them to enhance solution effectiveness.
  • Document processes, models, and systems to ensure transparency and reproducibility.
  • Design and implement automations to streamline internal workflows and enhance client-facing services.

Additional Duties
  • Collaborate with cross-functional teams to ensure seamless solution delivery.
  • Provide high-quality customer service and maintain strong client relationships.
  • Understand client business needs and align technology solutions accordingly.
  • Accurately track time, tasks, and expenses in the ticketing system.
  • Participate in customer interviews, feedback loops, and solution ideation.

Required Qualifications
  • Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field - or equivalent experience (e.g., GitHub projects, personal portfolio).
  • Strong programming skills in Python (preferred), Java, or C++.
  • Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.
  • Proficiency in data manipulation and analysis using Pandas, NumPy, and SQL.
  • Experience with cloud platforms (AWS, Azure, Google Cloud, OpenAI) and MLOps tools.
  • Solid understanding of algorithms, data structures, and software engineering principles.
  • Ability to work independently and collaboratively, with a strong sense of ownership and self-management.
  • Familiarity with NLP, computer vision, reinforcement learning, and large language models (LLMs).
  • Knowledge of data privacy, model interpretability, and ethical AI practices.
  • Contributions to open-source AI projects or published research are a plus.

Skills & Technologies
  • Scripting & Automation: PowerShell, Python (Jinja), Power Automate, REWST, Zapier
  • APIs: REST (required), SOAP (optional), OpenAPI spec, Postman
  • AI Techniques: Retrieval-Augmented Generation (RAG), AI scoring (Model Performance Metrics), reinforcement learning
  • LLM Platforms: OpenAI, Claude, Gemini
  • Microsoft 365 Stack: CoPilot, Power Automate, Function Apps, Email integrations
  • Cloud & Serverless: Azure Function Apps

Benefits (subject to eligibility and length of employment)
  • Health insurance allowance up to $400/month
  • Employer-paid group life insurance policy valued at $100,000
  • 3% employer match on retirement savings plan
  • Aflac individual accident insurance
  • High-speed internet reimbursement up to $40/month
  • $40/month cellular phone allowance
  • 8 paid holidays annually
  • Paid vacation: 5 days/year to start, increasing to 10 days/year after 3 years of service
  • Access to Safe Ride Home Program (Uber ridesharing)

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