Senior Software Engineer for RL Environment DevOps Workflows
Overview
Senior Software Engineer on a part-time contractor basis, remote worldwide. You’ll help train next-generation AI systems by creating reproducible reinforcement learning environments that evaluate how models handle real‑world DevOps and software workflows. Your focus is on domain expertise and quality inputs, not prior AI experience. You’ll work with languages like Python, C++, Java, Go, TypeScript, or Rust to shape model behavior and performance.
What You'll Do5
- 1Design and implement reinforcement learning environments that emulate complex software engineering workflows such as DevOps, CI/CD, and debugging tasks using familiar CLI tools like git, docker, gdb, asan, and ffmpeg
- 2Produce high-quality, reproducible test scenarios and provide a gold reference solution to guide model learning
- 3Debug and refactor code to improve maintainability and reliability across evolving codebases
- 4Contribute to feature development and codebase improvements with an eye for performance and scalability
- 5Collaborate with cross‑functional teams in a remote setting, documenting decisions and results clearly
Requirements7
- 1Proficiency in one or more of Python, C++, Java, Go, TypeScript, or Rust
- 2Strong grasp of algorithms, data structures, and performance tuning
- 3Proven debugging experience and delivering maintainable software solutions
- 4Background in feature development and codebase refactoring
- 5Track record of optimizing software for performance and scalability
- 6Excellent written and verbal communication with strong attention to detail
- 7Experience collaborating in remote, cross‑functional teams
Who Should Apply
The ideal candidate holds deep software engineering expertise across at least one of the listed languages and can translate complex workflows into testable RL environments. This role may not be suitable for someone who expects AI domain experience to be a prerequisite. Some candidates may score lower if they have limited experience with large distributed codebases, or if they lack strong collaboration skills in remote settings or clear technical documentation. Common rejection reasons include mismatched language experience, insufficient debugging background, or minimal exposure to DevOps‑level workflows.
Salary Insight
Pay is task-based and depends on the complexity of completed work; no hourly rate is published. Pay discussions occur after tasks and performance align with project specs.
Location
Required Skills
Application Tip
Highlight concrete results from past feature work or refactors, and point to any prior experience with large codebases and remote collaboration to demonstrate readiness for the RL environment project.
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1Application received
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2ATS + eligibility screening
We check your profile against the role’s skills, seniority, and requirements.
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