ZipRecruiter

Log In

2

Remote Reinforcement Learning Jobs (NOW HIRING)

Jobgether

You'll work closely with experienced engineers in a remote, collaborative environment where ... design, or reinforcement learning, including approaches such as GRPO, is highly desirable.

Centific

Applied Reinforcement Learning Engineer

Palo Alto, CA or Seattle, WA (Hybrid/Remote) About the Team Centific AI Research advances foundational AI models and applications through reinforcement learning, alignment, and human-centered ...

YO AI Labs

Machine Learning Engineer - Remote

Boston, MA · Remote

$80 - $120/hr

Remote Job Summary We are seeking experienced Senior Software Engineers to support an AI training ... Create reinforcement learning environments for software engineering tasks. * Design tasks involving ...

YO AI Labs

Machine Learning Engineer - Remote

Boston, MA · Remote

$80 - $120/hr

Remote Job Summary We are seeking experienced Senior Software Engineers to support an AI training ... Create reinforcement learning environments for software engineering tasks. * Design tasks involving ...

YO AI Labs

Machine Learning Engineer - Remote

Austin, TX · Remote

$80 - $120/hr

Remote Job Summary We are seeking experienced Senior Software Engineers to support an AI training ... Create reinforcement learning environments for software engineering tasks. * Design tasks involving ...

YO AI Labs

Machine Learning Engineer - Remote

Seattle, WA · Remote

$80 - $120/hr

Remote Job Summary We are seeking experienced Senior Software Engineers to support an AI training ... Create reinforcement learning environments for software engineering tasks. * Design tasks involving ...

YO AI Labs

Machine Learning Engineer - Remote

San Jose, CA · Remote

$80 - $120/hr

Remote Job Summary We are seeking experienced Senior Software Engineers to support an AI training ... Create reinforcement learning environments for software engineering tasks. * Design tasks involving ...

YO AI Labs

Machine Learning Engineer - Remote

Seattle, WA · Remote

$80 - $120/hr

Remote Job Summary We are seeking experienced Senior Software Engineers to support an AI training ... Create reinforcement learning environments for software engineering tasks. * Design tasks involving ...

YO AI Labs

Machine Learning Engineer - Remote

Miami, FL · Remote

$80 - $120/hr

Remote Job Summary We are seeking experienced Senior Software Engineers to support an AI training ... Create reinforcement learning environments for software engineering tasks. * Design tasks involving ...

YO AI Labs

Machine Learning Engineer - Remote

Phoenix, AZ · Remote

$80 - $120/hr

Remote Job Summary We are seeking experienced Senior Software Engineers to support an AI training ... Create reinforcement learning environments for software engineering tasks. * Design tasks involving ...

YO AI Labs

Machine Learning Engineer - Remote

Palo Alto, CA · Remote

$80 - $120/hr

Remote Job Summary We are seeking experienced Senior Software Engineers to support an AI training ... Create reinforcement learning environments for software engineering tasks. * Design tasks involving ...

next page

Showing results 1-20

All Jobsremote JobsRemote Reinforcement Learning Jobs

Remote Reinforcement Learning information

See salary details

$11K

$83.9K

$140K

How much do remote reinforcement learning jobs pay per year?

As of Sep 1, 2026, the average yearly pay for remote reinforcement learning in the United States is $83,885.00, according to ZipRecruiter salary data. Most workers in this role earn between $72,000.00 and $139,000.00 per year, depending on experience, location, and employer.

What is a remote reinforcement learning?

A Remote Reinforcement Learning job involves developing and applying reinforcement learning algorithms while working from a location outside of a traditional office environment. Professionals in this field focus on creating systems where agents learn optimal behaviors through trial and error, often using feedback from their environment. These jobs typically require expertise in machine learning, programming, and mathematics, and are commonly found in industries like robotics, gaming, and autonomous systems. Working remotely allows researchers and engineers to collaborate with global teams using digital tools and platforms.

What are the key skills and qualifications needed to thrive as a remote reinforcement learning engineer?

To thrive as a Remote Reinforcement Learning Engineer, you need a strong background in machine learning, statistics, and programming (especially Python), often supported by an advanced degree in computer science or a related field. Familiarity with frameworks such as TensorFlow, PyTorch, and RL-specific libraries like OpenAI Gym, along with experience using cloud computing platforms, is typically required. Excellent problem-solving skills, self-motivation, and effective remote communication help individuals excel in distributed teams. These skills ensure the successful design, implementation, and deployment of reinforcement learning solutions while collaborating efficiently in a remote work environment.

What are common challenges faced when working remotely in a reinforcement learning role and how can they be addressed?

Working remotely in a Reinforcement Learning role often involves overcoming communication barriers with cross-functional teams, managing large-scale experiments without on-site resources, and staying updated with rapidly evolving research. To address these challenges, it's important to establish regular check-ins with colleagues, utilize cloud-based platforms for experiment management, and participate in virtual seminars or journal clubs. Developing strong self-motivation and time management skills is also crucial to maintain productivity in a remote environment.

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

AspectRemote Reinforcement Learning
Required CredentialsMaster's or PhD in Computer Science, AI, or related fields; knowledge of RL algorithms
Work EnvironmentResearch-focused, experimental, often involves simulation and algorithm development
Employer & Industry UsageTech companies, research labs, AI startups focusing on autonomous systems
Common Search & Comparison IntentUnderstanding specialized AI roles, research focus, and technical skills

Remote Reinforcement Learning specialists focus on developing algorithms that enable machines to learn through trial and error in simulated or real environments. In contrast, Remote Machine Learning Engineers typically work on deploying and optimizing various machine learning models across applications. While both roles require strong programming skills and knowledge of AI, reinforcement learning emphasizes decision-making processes, whereas machine learning engineering covers a broader range of models and deployment strategies.

More about Remote Reinforcement Learning jobs

What cities are hiring for Remote Reinforcement Learning jobs?

Cities with the most Remote Reinforcement Learning job openings:

What are the most commonly searched types of Reinforcement Learning jobs?

The most popular types of Reinforcement Learning jobs are:

What states have the most Remote Reinforcement Learning jobs?

States with the most job openings for Remote Reinforcement Learning jobs include:

What job categories do people searching Remote Reinforcement Learning jobs look for?

The top searched job categories for Remote Reinforcement Learning jobs are:

Remote Reinforcement Learning jobs near you
Infographic showing various Remote Reinforcement Learning job openings in the United States as of August 2026, with employment types broken down into 79% Full Time, and 21% Contract. Highlights an 100% Remote job distribution, with an average salary of $83,885 per year, or $40.3 per hour.

Reinforcement Learning Engineer (Cybersecurity)

Bugcrowd

Remote

$176K - $242K/yr

Full-time

Re-posted 25 days ago

Job description

Job Summary

The Bugcrowd RL and Reasoning Team focuses on pushing the boundaries of autonomous cybersecurity by building authentic reinforcement learning environments for foundational model companies. As a Reinforcement Learning Engineer  you will advance the frontier of AI Reinforcement Learning development and delivery.  You will build the infrastructure and tooling that transforms real-world vulnerability research into large-scale reinforcement learning environments used to train next-generation AI systems.

This role is unique. You will help create the training environments that teach AI systems how to hack and defend software. Your work will directly influence the capabilities of the next generation of AI models. Instead of building a single application, you will build the infrastructure that generates thousands of environments used to train frontier AI systems.

Our team works at the intersection of AI, security research, and systems engineering, building environments that allow models to learn skills such as vulnerability discovery, exploitation, and remediation. 

Essential Duties and Responsibilities 

If you enjoy building high-performance systems that power cutting-edge AI research, this role is for you.

This role focuses on building the systems that generate RL environments, not just the environments themselves. You will design pipelines that ingest software projects, analyze them with Bugcrowd's Mayhem platform, and automatically construct training environments used by frontier AI labs including Anthropic, OpenAI, and Cohere.

The ideal candidate is a strong systems engineer who understands:

  • Reinforcement learning workflows
  • Building clean, reproducible Linux ML environments (containers, MCP, etc)
  • System security background in binary exploitation, such as buffer overflows, fuzzing, exploitation, and x86/64.
  • Experience developing applications in Python and C, with Rust a plus. 

Education, Experience, Knowledge, Skills, and Abilities

Understanding of RL training workflows used by modern LLM systems

  • Experience with DevOps pipelines (e.g., github actions), reproducible builds (docker, buildkit, nix).
  • Proficiency in Python and C. Other languages (especially Rust) are a plus.
  • Understanding of software vulnerabilities, fuzzing, or program analysis
  • Experience with build systems and large open-source codebases
  • Comfort working with Linux systems and low-level debugging
  • Experience working with benchmark environments (CTFs, SWE-bench, security challenges, etc.) is a plus

Working Conditions and Physical Requirements

The ideal candidate must be able to complete all physical requirements of the job with or without reasonable accommodation.

Sitting and / or standing - Must be able to remain in a stationary position 50% of the time

Carrying and / or lifting - Must be able to carry / move laptop as needed throughout the work day.

Environment - remote, work-from-home 100% of the time.

Pay Range Disclosure

At Bugcrowd, we strive for fairness, equality and to create an environment that allows our people to perform at their very best. Our compensation philosophy is to foster a collaborative community that rewards, attracts and retains the best possible talent. The provided salary details are based on US national averages and we retain the flexibility to tailor to the needs of the business.

The national estimate for the current base range for the position of $176,400 - $242,550.

This position may also be eligible to participate in a discretionary bonus program or commission plan, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Apply