Terminal has partnered with Outlier—part of Scale AI, a leader in AI training and data infrastructure—to connect our engineering talent with high-quality, flexible opportunities in AI development. Through this partnership, we refer qualified candidates to Outlier’s global platform, where you can contribute to training advanced AI systems by applying your technical expertise. Projects may include evaluating and improving model outputs, writing or reviewing code, and helping AI systems produce more accurate, reliable results.

Outlier supports a global network of over 100,000 experts working remotely on flexible schedules. This is paid, project-based work designed to fit alongside your existing commitments—whether you’re between roles, exploring new opportunities, or simply looking to stay sharp.

No prior experience in AI is required. What matters most is strong domain expertise and a thoughtful, detail-oriented approach. If you’re interested, Terminal will facilitate your referral and help you get started!

Outlier is looking for skilled software experts to help train generative AI models. This freelance role is fully remote and offers flexible hours—you can contribute whenever it fits your schedule.

• Developing objective, verifiable criteria (rubrics) to evaluate system performance and ensure outputs meet strict functional requirements. • Reviewing system logs and "trajectories" to refactor code, improve execution paths, and reach a "Golden Path" of perfect reliability • Testing systems for vulnerabilities, including improper data exposure, unauthorized access escalations, and edge-case failures.

• 2+ years of experience in backend engineering, AI automation, or complex systems integration • Proven ability to build and maintain production-grade software with modular separation (e.g., distinct services for data parsing, logic processing, and reporting) • Strong command of at least two major languages (e.g., Python, JavaScript, Go, or Java) and experience working with SQL databases • Practical experience building for live, non-mocked environments and handling multi-turn system interactions. • Outstanding attention to detail and the ability to provide clear, high-density technical feedback on complex system behaviors Nice to Have • Expertise building multi-stage coordination tasks where data acquisition leads to reasoned output • Hands on experience integrating agents with live tools such as Supabase, Gmail, and various APIs to solve real-world problems • High level of comfort implementing persistent state and session discovery using MEMORY.md to track agent progress. • Experience identifying subtle failures like privacy leaks, authority escalation, or indirect prompt injections.