We are hiring a Competitive Programming Specialist to create terminal bench–style problems and tasks involving agents within a competitive programming environment, as part of a hiring effort for its AI lab partner building advanced agent-based infrastructure. This role is ideal for coders with a strong background in algorithmic thinking, problem design, and hands-on experience with competitive programming platforms. You'll be developing interactive, terminal-based challenges that test the problem-solving capabilities of autonomous agents in real-time coding scenarios. You’re a great fit if you: Have a track record of success in competitive programming contests (e.g., ICPC, Codeforces, LeetCode, AtCoder, HackerRank). Possess strong skills in algorithms, data structures, and systems-level thinking. Are proficient in Python, C++, or Go, and comfortable working in terminal-based coding environments. Can design programming problems that test time complexity, memory constraints, logic correctness, and multi-step reasoning. Have experience with online judge systems, sandboxed environments, or contest infrastructure. Are curious about AI agents and interested in how agents can solve real-world programming tasks. Enjoy creating reproducible, progressive challenges and can abstract real-world systems problems into code-based puzzles. Primary Goal of This Role To create terminal bench–style problems and tasks where autonomous agents are challenged to solve competitive programming problems in a live, terminal-driven environment. These tasks will test agent performance across algorithmic domains — such as graph theory, dynamic programming, greedy techniques, and real-time debugging — and serve as a benchmark for reasoning, adaptability, and correctness under constraints. What You’ll Do Design and implement terminal-based coding challenges for agents to solve autonomously. Build a sandboxed, judge-like environment that runs test cases, checks correctness, and monitors time/memory usage. Simulate real-world competitive conditions: limited time, incremental hints, multiple submissions, etc. Collaborate with AI engineers to define reward functions, failure conditions, and difficulty tiers. Develop tooling for benchmark resets, output validation, and scenario generation. Evolve the difficulty of problems from beginner-level syntax and logic to advanced algorithmic pipelines and systems simulations. Why This Role Is Exciting Define a new generation of programming benchmarks built specifically for AI agents. Blend algorithmic design, problem solving, and systems-level realism in one role. Work on uncharted challenges that push the boundaries of what agents can understand and execute. Pay & Work Structure You’ll be classified as an hourly contractor. Paid weekly via Stripe Connect, based on hours logged. Part-time (20 hrs/week) with fully remote, async flexibility — work from anywhere, on your own schedule. We consider all qualified applicants without regard to legally protected characteristics and provide reasonable accommodations upon request.
Hiring an Optimization Specialist t o design and implement optimization models and heuristics that solve large-scale real-world scheduling, routing, and allocation problems, and deliver them as reproducible, production-grade pipelines for AI-driven systems. You’re a great fit if you: Have a background in operations research, applied mathematics, computer science, or engineering . Are proficient in Python and optimization libraries such as CVXPY, OR-Tools, CPLEX, SciPy, NumPy, and pandas . Understand mathematical programming methods (MILP, CP, heuristics) and their tradeoffs. Have experience designing models for scheduling, routing, or allocation at scale. Are comfortable building reproducible pipelines and benchmarking optimization approaches. Care about delivering models that balance optimality, scalability, and real-world performance . Are curious about how optimization connects with AI systems and large-scale decision engines . What You’ll Do Build scalable optimization pipelines for scheduling, routing, and resource allocation. Translate AI lab and product requirements into robust optimization formulations (MILP/CP, heuristics). Benchmark, validate, and stress-test optimization models with real-world datasets. Develop heuristics and approximation methods for time-sensitive and large-scale workloads. Collaborate with AI researchers and engineers to integrate optimization into production systems. Document models, experiments, and workflows for reproducibility and reliability. Why This Role Is Exciting You’ll pioneer optimization pipelines that power AI systems in production . You’ll apply cutting-edge mathematical programming techniques to high-impact, real-world problems . You’ll collaborate on a high-impact effort at the intersection of optimization, AI, and large-scale engineering . You’ll help shape how advanced optimization drives the next wave of AI research and applications .