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Reinforcement Learning Engineer (Cybersecurity)

Bugcrowd

LocationUnited States
Senioritymid_senior
CompanyBugcrowd
Verified recentlyChecked today
Compensation

$176k-$243k

Salary details are shown when available from the source listing. Sign in before applying so the role can be reviewed against your resume, salary goals, seniority, timezone, and location eligibility.

Requirements and working style

Decision details from the source listing

Schedule

fixed

These fields are normalized from the employer's text. Confirm details on the employer site before applying.

WFH.team analysis

What this posting tells you

Bugcrowd is hiring a full-time Reinforcement Learning Engineer (Cybersecurity) based in the US with a remote work policy (US only). The engineer will build infrastructure and tooling for RL environments used in AI cybersecurity applications. Required skills include reinforcement learning workflows, Linux environments, system security including binary exploitation and fuzzing, Python and C programming; Rust is a plus. Experience with DevOps pipelines, reproducible builds, and software vulnerabilities is expected. The role is 100% remote within the US. Salary range is $176,400 to $242,550 yearly base pay. No visa sponsorship or education requirements explicitly stated. The schedule is fixed remote work.

Role lane

Backend, Customer success, Data, Design and creative, DevOps, Legal, Marketing, Operations, Product, Security, Software

Where you can work

United States

Working hours

Timezone overlap is not stated.

Arrangement

mid_senior · full_time

Required signals
Reinforcement learning workflowsLinux ML environmentsContainersMCPSystem securityBinary exploitationBuffer overflowsFuzzingExploitationx86_64PythonCRustDevOps pipelinesGitHub ActionsReproducible buildsDockerBuildkitNixSoftware vulnerabilitiesProgram analysisBuild systemsLinux systemsDebugging
Preferred signals
RustBenchmark environmentsCTFsSWE-benchSecurity challenges
Confirm before applying
  • Required timezone overlap is not stated
Market context

Backend hiring on WFH.team

3,710active related roles
2,242new in the latest period
168.9jobs per 100 candidates
$202kmedian of comparable listed ranges

This role's listed pay is near the median among 200 comparable roles shown here. Category counts come from WFH.team's latest published remote job market snapshot.

Explore the remote job market
Skills and signals
Reinforcement learning workflowsLinux ML environmentsContainersMCPSystem securityBinary exploitationBuffer overflowsFuzzingExploitationx86_64PythonCRustDevOps pipelinesGitHub ActionsReproducible buildsRemote - US
Job description

Reinforcement Learning Engineer (Cybersecurity) at Bugcrowd

We are Bugcrowd. Since 2012, we’ve been empowering organizations to take back control and stay ahead of threat actors by uniting the collective ingenuity and expertise of our customers and trusted alliance of elite hackers, with our patented data and AI-powered Security Knowledge Platform™. Our network of hackers brings diverse expertise to uncover hidden weaknesses, adapting swiftly to evolving threats, even against zero-day exploits. With unmatched scalability and adaptability, our data and AI-driven CrowdMatch™ technology in our platform finds the perfect talent for your unique fight. We aim to create a new era of modern crowdsourced security that outpaces threat actors. Unleash the ingenuity of the hacker community with Bugcrowd, visit www.bugcrowd.com. Based in San Francisco and New Hampshire, Bugcrowd is supported by General Catalyst, Rally Ventures, Costanoa Ventures, and others.

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.

Culture

  • At Bugcrowd, we understand that diversity in the workplace is vital to a company’s success and growth. We strive to make sure that people are included and have a sense of being part of making Bugcrowd not only a great product but a great place to work.
  • We regularly hear from both customers and researchers that Bugcrowd feels like a family, and we strive to maintain that internally as well.
  • Our team consists of a broad range of people: musicians, adventure sports junkies, nature lovers, parents, cereal enthusiasts, night owls, cyclists, artists—you get the point.

At Bugcrowd, we are solving security threats and vulnerabilities that are relevant to everyone, therefore we believe solving these problems takes all kinds of backgrounds. We value the perspectives and experiences people from underrepresented backgrounds bring.

Disclaimer

This position has access to highly confidential, sensitive information relating to the technologies of Bugcrowd. It is essential that the applicant possess the requisite integrity to maintain the information in the strictest confidence.

The company is authorized to obtain background checks for employment purposes under state and federal law. Background checks will be conducted for positions that involve access to confidential or proprietary information (including trade secrets).

Background checks may include Social Security verification, prior employment verification, personal and professional references, educational verification, and criminal history. Applicants with conviction histories will not be excluded from consideration to the extent required by law.

Any personal data you submit in connection with your application will be processed in compliance with Bugcrowd's Privacy Policy, which you may review here: https://www.bugcrowd.com/privacy .

Equal Employment Opportunity

Bugcrowd is EOE, Disability/Age Employer.

Individuals seeking employment at Bugcrowd are considered without regards to race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, or sexual orientation.

Bugcrowd is committed to the full inclusion of all qualified individuals. In keeping with our commitment, Bugcrowd will take the steps to assure that people with disabilities are provided reasonable accommodations. Accordingly, if reasonable accommodation is required to fully participate in the job application or interview process, to perform the essential functions of the position, and/or to receive all other benefits and privileges of employment, please contact HR at ADA at bugcrowd.com.

Apply at: https://www.bugcrowd.com/about/careers/

Company context

Working remotely at Bugcrowd

Bugcrowd is hiring for 1 active remote role, with remote-friendly openings, application links, and job details refreshed from the public remote job inventory.

Headquarters
India, Costa Rica, United States, and Australia
Team size
51-200
Founded
2012
Remote policy

Remote hiring signal is inferred from active confirmed-remote job listings.

Application process

Review current openings on Bugcrowd's official careers page before applying.

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Remote Reinforcement Learning Engineer (Cybersecurity) at Bugcrowd | WFH.team