Highlights
Flexible, remote work, competitive hourly rates, opportunity to shape the future of agentic AI.
Description
Job Summary
pWe are seeking an experienced ML Engineer to join our team and help design, evaluate, and shape the future of autonomous AI agents. The ideal candidate will have a deep understanding of large language models (LLMs) and be skilled in writing evaluation rubrics, debugging agent traces, and providing high-density technical feedback for LLM training.
Responsibilities
- Write evaluation rubrics with objective pass/fail criteria
- Debug agent traces to identify failure patterns
- Stress test agents against edge cases, prompt injection, and tool misuse
- Assess production-grade modular software architecture
- Analyse multi-turn system interactions and behaviours
Required Skills
- Expertise in AI automation
- Modular software architecture design
- Proficiency in Python, JavaScript or Go
- Experience with SQL databases
- Multi-turn system interaction handling
Required Skills Explained
- Experience in backend engineering, AI automation, or complex systems integration
- Proven ability to build and maintain production-grade software with modular separation
- Strong command of at least two major languages such as Python, JavaScript, Go, or Java
- Experience working with SQL databases
- P practical experience building for live, non-mocked environments and handling multi-turn system interactions
Who is this for
pThis role is ideal for backend engineers with a focus on AI and complex systems. You should have experience building and maintaining production-grade software and be comfortable working in a remote environment.
Why This Job is a Good Opportunity
ulliOpportunity to shape the future of agentic AI systems by providing expert human feedback to leading AI organizations.liRemote work with flexible task assignments that allow for work-life balance.liPotential for high earnings based on experience and task complexity, paid weekly via supported payout platforms.liContribution to cutting-edge technology in the field of large language models (LLMs).
Interview Preparation Tips
- Research leading AI organizations to understand the current landscape and specific needs they have for their AI systems.
- PRACTICE AI Agent Evaluation with sample scenarios to be prepared for writing evaluation rubrics, debugging agent traces, and stress testing against edge cases.
- Become familiar with modular software architecture and its implementation in real-world applications.
- Prepare examples of how you have successfully built production-grade software and handled multi-turn system interactions.
Career Growth in This Role
pThe role of an ML Engineer offers significant opportunities for career growth, especially as the field of AI continues to evolve. As you gain experience, you can move into more complex projects involving larger and more sophisticated systems. You may also have the chance to specialize further within specific areas like health or education technology. Additionally, with proven skills in building production-grade software, you could transition into leadership roles or even start your own AI consultancy.
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Skills
Frequently Asked Questions
What is the compensation structure?Compensation ranges from USD $30–$50 per hour, with weekly payments via supported payout platforms.
Is this a full-time or part-time position?This is a fully remote, flexible role that can accommodate various workloads and schedules.
What kind of projects will I be working on?You'll be working with LLMs across various domains such as health, education, and daily life, evaluating AI agents and providing technical feedback.
