Java Backend Engineer

Role Overview :

Turing is seeking experienced Java engineers to partner with a leading AI research lab in building datasets and evaluation pipelines that improve next-generation AI models. In this role, you’ll deliver clean, scalable services in Java, review and refine AI-generated code, and design verification strategies that directly shape how AI-powered systems perform in real-world environments.

This is a fully remote, highly flexible engagement — work from anywhere, on your own schedule — while earning up to $100 / hr. It’s a rare opportunity to apply your Java expertise at the cutting edge of AI research and development.

What You’ll Do :

Build and maintain robust Java services and tools for AI training and evaluation.

Run benchmark tasks, evaluate outputs, and document precise rationales.

Refine AI-generated solutions and contribute to next-gen datasets (SFT / RLHF).

Collaborate with AI researchers and engineers to enhance product reliability and performance.

What We’re Looking For :

Strong professional experience with Java (language, tooling, testing, performance).

Skilled in secure, modular, testable backend design.

Familiarity with modern development workflows and best practices.

Excellent problem-solving skills and clear communication in English.

Bonus : experience with QA / test planning or large-scale evaluation systems.

Why You'll Love This Role :

Remote & Flexible → Work from anywhere, on your schedule.

Great Pay → Up to $100 / hr.

Career Edge → Gain experience at the intersection of Java and AI.

High-Impact Work → Your code directly shapes frontier AI systems

About Turing :

Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. Turing supports customers in two ways : first, by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialize in software engineering, logical reasoning, STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L.

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