About Us:
- 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.
Ideal Background:
- This role is ideal for engineers who have worked at the frontier of AI — at companies like OpenAI, NVIDIA, Databricks, Palantir, Snowflake, or similar organizations pushing the boundaries of intelligent systems.
- We especially welcome graduates from leading programs such as Harvard, Columbia, Princeton, Yale, University of Pennsylvania, and comparable institutions — though exceptional experience and skill always take precedence over pedigree.
Project Overview:
- As a Software Engineering evaluator, you will create cutting-edge datasets for training, benchmarking, and advancing large language models, collaborating closely with researchers.
- This includes curating code examples, providing precise solutions, and making corrections in Python, C/C++, Rust, Go, Java, and JavaScript (including ReactJS) — with particular emphasis on systems-level code, performance-critical applications, and infrastructure.
- You will evaluate and refine AI-generated code for efficiency, scalability, and reliability, and work with cross-functional teams to enhance enterprise-level AI-driven coding solutions.
- What Does a Typical Day Look Like?
- Work on AI model training initiatives by curating code examples, building solutions, and correcting code in Python, C/C++, Rust, Go, Java, and JavaScript (including ReactJS).
- Evaluate and refine AI-generated code with an emphasis on systems-level correctness, performance, and reliability.
- Collaborate with cross-functional teams to enhance AI-driven coding solutions against industry performance benchmarks.
- Build agents that can verify the quality of systems-level and infrastructure code and identify error patterns.
- Hypothesize on steps in the software engineering cycle (prototyping, architecture design, API design, production implementation, launch, experiments, monitoring, operational maintenance) and evaluate model capabilities on them.
- Design verification mechanisms that can automatically verify a solution to a software engineering task.
Required Skills:
- Several years of software engineering experience (3 years or more).
- Strong expertise in systems programming, infrastructure, or backend development using languages like JS, Python, C/C++, Rust, and Go.
- Experience building and deploying scalable, production-grade software using modern languages and tools.
- Deep understanding of software architecture, design, development, debugging, and code quality/review assessment.
- Excellent oral and written communication skills for clear, structured evaluation rationales.
Engagement Details:
- Commitment: flexible engagement, minimum 10 hrs/week, up to 40 hrs/week.
- Type: Contractor (no medical/paid leave).
- Duration: 1 month (potential extensions based on performance and fit).
- Location: Candidates must be based in the United States.
- Evaluation Process:
- The application process takes 15–30 minutes.
- Completion of an AI video interview is required.