Senior Software Engineer, AI Evaluation Infrastructure

• Review teammates’ pull requests against our engineering guidelines and help keep the codebase consistent.

What you bring

• Typically 5+ years building and operating production backend systems, with ownership of at least one service from design through on-call.

• Strong Python. Experience with Django (or a similar framework), PostgreSQL, and a task queue such as Celery. What matters most is having run a real system, not knowing a particular framework.

• Hands-on experience in LLM evaluation, beyond calling a model API. You understand how a benchmark task is built, how an agent trial is scored, and how results are aggregated and compared. Experience with Harbor, Terminal-Bench, SWE-bench, Inspect, or a similar harness is a strong plus.

• Judgment about task quality. You can spot ambiguous instructions, weak or gameable verifiers, leaked answers, and checks that pass for the wrong reason.

• Good tradeoffs. You reach for the smallest design that solves the problem, extend what already exists before adding something new, and can explain what you chose not to build.

• Ownership. You take a fuzzy request, find the relevant code, ask questions only when the answer changes the design, and finish the job, including migrations, tests, and edge cases users will hit.

• Quick adoption of team conventions. You read the written guidelines and your first pull requests already match them in naming, structure, tests, and error handling.

• Comfort with a TypeScript and React frontend when a change is visible there. You don’t need to be a frontend specialist.

• Clear writing. Your pull request descriptions and design notes explain why, not just what.

Nice to have

• Experience running agents in sandboxed or containerized environments (Docker, Kubernetes, or cloud sandboxes such as Modal or Daytona).

• Experience with LLM-as-a-judge or rubric-based grading, and with reducing judge bias and noise.

• Familiarity with coding agents such as Claude Code, Codex, or OpenHands, and with MCP.

• Experience with distributed job scheduling, concurrency limits, or database locking at scale.

• Contributions to open-source evaluation or infrastructure projects.

How we work

• Written engineering guidelines, applied consistently, with the same review bar for everyone.

• Business logic lives in services. Hot paths stay cheap. Lint and tests pass before a pull request is ready.

• The same vocabulary in the code, the API, and the UI.

• We prefer deleting code to adding it, and simple designs to clever ones.

A strong first month looks like several changes merged with light review, and one area of the system you can change confidently without a guide.

Interview process

• A short conversation about a system you built and the tradeoffs you made.

• A practical exercise: a focused change in an existing codebase.

• A discussion of a flawed benchmark task: what’s wrong with the instruction, the verifier, and the scoring.

• A conversation with the team.

Values

• We are client first: We put our clients at the center of everything we do, because their success is the ultimate measure of our value.

• We work at Start-Up Speed: We move fast, stay agile and favor action because momentum is the foundation of perfection

• We are AI forward: We help our clients build the future of Al and implement it in our own roles and workflow to amplify productivity.

Advantages of joining Turing

• Work at the frontier of AI , helping the world’s leading AI labs improve their most advanced models by building expert datasets, RL environments, and first-of-a-kind benchmarks.

• Contribute to leading-edge AI research and showcase your work at top conferences such as ICLR, ICML, and NeurIPS.

• Bring frontier AI innovation to the enterprise , applying lessons learned from leading AI labs to solve real-world business challenges.

• Collaborate with and learn from exceptional colleagues with deep AI experience from Google, Meta, Amazon, and other leading technology companies.

• Move at the pace of AI innovation , with the speed, ownership, and impact of a startup.

Turing is proud to be an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, disability, protected veteran status, or any other legally protected characteristics. At Turing we are dedicated to building a diverse, inclusive and authentic workplace and celebrate authenticity, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles.

For applicants from the European Union, please review Turing's GDPR notice here .

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Source: Turing careers page