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Openai Reinforcement Learning Jobs (NOW HIRING)

Cypress HCM

LLM Research Engineer

Mountain View, CA · On-site

$90 - $121.86/hr

Familiarity with Hugging Face libraries and OpenAI APIs. * Experience with MLOps tools like Docker ... Knowledge of reinforcement learning and RLHF (Reinforcement Learning with Human Feedback)

Gradial

Applied AI Engineer

Seattle, WA · On-site

... applying reinforcement learning to end-to-end agent systems. • Design modular frameworks for ... OpenAI APIs, Anthropic APIs). • Practical understanding of LLMs, prompt engineering and agentic ...

OpenAI

SOC Architect

San Francisco, CA · On-site

$266K - $445K/yr

... OpenAI is to discover and enact the path to safe, beneficial AGI. To do this, we believe that many technical breakthroughs are needed in generative modeling, reinforcement learning, large scale ...

Gradial

Applied AI Engineer

Seattle, WA · On-site

... applying reinforcement learning to end-to-end agent systems. • Design modular frameworks for ... OpenAI APIs, Anthropic APIs). • Practical understanding of LLMs, prompt engineering and agentic ...

Gradial

Applied AI Engineer

Seattle, WA · On-site

... applying reinforcement learning to end-to-end agent systems. • Design modular frameworks for ... OpenAI APIs, Anthropic APIs). • Practical understanding of LLMs, prompt engineering and agentic ...

OpenAI

Researcher, Alignment Oversight

San Francisco, CA · On-site

$250K - $445K/yr

Have experience with reinforcement learning, post-training, preference optimization, scalable ... About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general ...

Purple Drive Technologies

GenAI Architect

Seattle, WA · On-site

$72.50 - $93.25/hr

Agentic workflows, multi-agent systems, reinforcement learning * Frameworks: LangChain/LangGraph, Crew AI, Semantic Kernel, OpenAI Agentic SDK * Programming & ML Libraries: * Python, SQL * TensorFlow ...

Gradial

Applied AI Engineer

Seattle, WA · On-site

$130K - $220K/yr

OpenAI APIs, Anthropic APIs). * Practical understanding of LLMs, prompt engineering and agentic ... Background in reinforcement learning or data-centric AI approaches. Compensation The salary range ...

IT America Inc

Agentic AI Engineer Lead

Dallas, TX · On-site

$101K - $133K/yr

... AutoGen, OpenAI The Agentic AI Lead is a pivotal role responsible for driving the research ... Apply reinforcement learning (RLHF/RLAIF) methodologies to fine-tune AI agents for improved ...

IT360, Inc.

AI Engineer

Peoria, IL

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

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Openai Reinforcement Learning information

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$28.5K

$58.3K

$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.

Artificial Intelligence (AI) Engineer

TechSur Solutions

Reston, VA • On-site, Remote

$119K - $143K/yr

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

Company Description

TechSur Solutions is a digital services company whose mission is to enable digital transformation for our customers to improve quality and efficiency. Based in the DC metropolitan area, TechSur specializes in advanced cloud services, modernization for both IT structures and applications, leveraging Agile development, and Data Analytics. Since we were formed in August of 2016, we have supported multiple impactful and exciting government programs.

Job Description

Role:   Artificial Intelligence (AI) Engineer

Client:   US Courts

Duration:  Full time position 

Location: Reston, VA (Hybrid - 3x/Week)

Company Overview

TechSur Solutions is a digital services company whose mission is to enable digital transformation for our customers improving quality and efficiency. Based in the DC metropolitan area, TechSur specializes in advanced cloud services, modernization for both IT structures and applications, leveraging Agile development, and Data Analytics. Since we were formed in August of 2016, we have supported multiple impactful and exciting government programs.

Job Description

We are seeking a highly motivated AI Engineer with a strong focus on OpenAI technologies to join our growing team. The ideal candidate will have a deep understanding of AI models, multi-agent systems, and the ability to design, develop, and implement intelligent agents capable of autonomous problem-solving and decision-making. Your work will contribute to creating innovative AI-driven applications and solutions that integrate cutting-edge advancements in artificial intelligence, including GPT models, reinforcement learning, and natural language processing.

Job Responsibilities

  • Design and develop AI agents leveraging OpenAI's GPT models and APIs to solve complex problems in real-world environments.
  • Collaborate with cross-functional teams to integrate AI agents into products, services, and tools.
  • Implement and fine-tune natural language processing (NLP) capabilities for AI agents, improving their comprehension and interaction with users.
  • Develop autonomous, multi-agent systems capable of communicating, learning, and collaborating to perform tasks and achieve goals.
  • Create pipelines for training, fine-tuning, and deploying AI models on various platforms, ensuring scalability and efficiency.
  • Research and integrate reinforcement learning techniques to improve agent performance and adaptability.
  • Analyze, debug, and optimize AI agents for performance, robustness, and scalability.
  • Stay current with the latest advancements in AI, ML, and NLP, particularly OpenAI's technology stack.
  • Contribute to creating best practices and documentation for the development and deployment of AI agents.

Required Skills/Qualifications

  • 3+ years of experience in AI/ML development, with a focus on AI agents, multi-agent systems, or autonomous systems.
  • Strong experience with OpenAI GPT models, APIs, and NLP technologies.
  • Proficiency in Python and familiarity with AI/ML frameworks such as TensorFlow, PyTorch, or similar.
  • Hands-on experience with reinforcement learning, deep learning, or generative models.
  • Familiarity with cloud platforms (e.g., AWS, GCP) and containerization tools (e.g., Docker, Kubernetes).
  • Strong problem-solving skills and the ability to work in a fast-paced, collaborative environment.
  • Excellent written and verbal communication skills, with the ability to explain technical concepts to non-technical stakeholders
  • Strong programming skills in languages such as Python, R, or Java.
  • Experience with AI/ML frameworks and libraries such as TensorFlow, Keras, PyTorch, or scikit-learn.
  • Strong problem-solving skills and the ability to work on multiple projects simultaneously.
  • Excellent communication and teamwork abilities.

Preferred Experience

  • Experience with large-scale model deployment in production environments.
  • Knowledge of ethical AI development practices and responsible AI usage.
  • Prior experience in developing conversational agents, virtual assistants, or autonomous systems.
  • Understanding of multi-agent coordination and communication protocols.
  • Passion for cutting-edge AI technologies and their applications.
  • Experience working with federal clients or within the government sector is preferred.
Qualifications

Education

  • Bachelor’s or master’s degree in computer science, Data Science, Artificial Intelligence, or a related field
  • Years of experience can be considered in lieu of degree

Additional Information

All your information will be kept confidential according to EEO guidelines.