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ML/AI Systems Engineer
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About the Role
We are building LLM evaluation and training datasets to train LLM to work on realistic software engineering problems. One of our approaches in this project is to build verifiable SWE tasks based on public repository histories in a synthetic approach with human-in-the-loop; while expanding the dataset coverage to different types of tasks in terms of programming language, difficulty level, and etc. Turing is seeking a Senior AI Systems Engineer with deep expertise in multi-step agentic architecture to support a high-impact, exploratory mathematics research initiative.
What You'll Do
- Design, build, and optimize multi-step agentic workflows capable of multi-hop reasoning, hypothesis generation, and technical validation.
- Collaborate closely with mathematical researchers to translate complex, abstract proofs into structured technical specifications and automated pipelines.
- Develop reusable architectural frameworks, tooling, and memory systems for STEM-focused AI agents.
- Evaluate and iterate on agent performance, ensuring high accuracy, reliability, and trace logic across execution steps.
- Technical Expertise: Proven track record of architecting and deploying production-grade, multi-step agentic systems (e.g., using frameworks like LangGraph, AutoGen, CrewAI, or custom orchestration).
- Domain Experience: Background building AI/ML applications within STEM domains (Mathematics, Physics, Computer Science, or Quantitative Finance).
- Core Skills: Advanced Python proficiency, experience with LLM orchestration, structured output generation, tool integration, and state management.
- Problem-Solving: Comfort working alongside subject-matter experts to translate dense academic material into modular software systems.
You're a Good Fit If You
- Required skills: MATLAB
Role Highlights
Pay & Payout
Independent contractor engagement through Turing. Apply via the link below - Turing handles vetting, onboarding and payment.
Common Questions
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