Urgent hire: ASAP start, 4 week contract. Applications reviewed on a rolling basis, apply early. Main tasks listed: Use AI coding agents throughout development, QA, and validation; Participate in onboarding, calibration, and quality reviews; deliver to the quality bar on agreed milestones.
In this role, you will work on cutting-edge initiatives to fine-tune large language models by leveraging your deep analytical skills and mathematics expertise. The ideal candidate possesses a strong foundation in Mathematics —spanning advanced engineering entrance levels through graduate and PhD-level concepts—and the ability to break down complex phenomena into clear, step-by-step reasoning. Main tasks listed: In this role, you will help set the benchmark for AI capabilities in advanced physical sciences. Your day-to-day responsibilities will include:; Problem Creation & Solutioning: Designing and solving challenging physics problems that test the boundaries of large language models; Authoring Gold-Standard Data: Creating clear, high-quality, step-by-step solutions with detailed and articulated reasoning; Research Collaboration: Working with LLM researchers to align task designs with evaluation goals, targeting key areas where models struggle (e.g., symbolic manipulation, abstraction, multi-step reasoning).
We are looking for participants based in South Korea to support a project involving Google Wallet and Plaid. Main tasks listed: Follow the project instructions and complete assigned tasks using Google Wallet and Plaid; Provide accurate information about the account setup and task experience; Report any issues encountered during the process; Maintain confidentiality regarding all project-related information.
We are looking for an engineer to build and deploy an intelligent, autonomous operations agent that supervises our data pipeline infrastructure around the clock. The agent will predict delivery delays before they occur, verify data quality using adaptive statistical baselines, and synthesize code-level fixes for routine operational failures. You will own the agent end to end, from design and evaluation to production reliability.
We are looking for participants based in Japan to support a project involving Google Wallet and Plaid. Main tasks listed: Follow the project instructions and complete assigned tasks using Google Wallet and Plaid; Provide accurate information about the account setup and task experience; Report any issues encountered during the process; Maintain confidentiality regarding all project-related information.
Commitments Required: At least 6 hours per day and a minimum of 40 hours per week, with a 4-hour overlap with PST. Employment Type: Contractor assignment; no medical or paid leave. Main tasks listed: Design challenging, realistic agentic scientific workflows across the life sciences; Create tasks requiring multiple computational steps rather than single-script or simple question-and-answer solutions; Develop realistic input files, scientific datasets, instructions, constraints, and expected deliverables; Build tasks requiring agents to inspect data, select appropriate methods, execute analyses, troubleshoot problems, and synthesize results.
We’re looking for experienced security engineers to evaluate how effectively static analysis tools detect vulnerabilities in GenAI applications. You’ll build small, runnable agent and RAG codebases containing realistic examples of Sensitive Information Disclosure and Excessive Agency, along with fixed and near-miss versions. You’ll then trace, annotate, test, and explain each finding. Main tasks listed: Build runnable agent/RAG repositories with code-reachable Sensitive Information Disclosure or Excessive Agency vulnerabilities across tool calling, memory, and MCP; Create vulnerable, fixed, and hard-negative variants with minimal security-relevant differences; Trace and annotate assets, data/action paths, controls, root causes, severity, and residual risk; Define authorization contexts and write deterministic tests validating vulnerable, fixed, and negative behavior.
We are looking for a Software Engineer with hands-on experience in full-stack development and some exposure to DevOps practices. You will contribute to building and operating applications that support critical engineering workflows. This role is ideal for someone who can independently deliver features, understands how systems run in production, and is looking to grow into owning services end-to-end. Main tasks listed: Design, develop, and maintain full-stack applications using React, TypeScript, and Python Build and enhance backend APIs and services for scalability and performance Collaborate with engineers and stakeholders to define and deliver technical solutions Participate in code reviews and contribute to improving engineering standards Debug and resolve issues across frontend, backend, and deployment environments Work with cloud platforms to deploy and operate applications Contribute to CI/CD pipelines and improve development and release workflows Help improve observability, monitoring, and reliability of applications.
We are seeking Life Sciences Subject Matter Experts to design advanced scientific-reasoning tasks for LifeSciBench. This is a non-coding role focused on biological knowledge, experimental interpretation, data analysis, and rigorous scientific reasoning. You will create challenging, objectively defensible problems based on realistic research scenarios, experimental results, biological data, figures, sequences, structures, and literature-style evidence. Main tasks listed: Design novel, graduate-level life sciences problems grounded in realistic research contexts; Develop clear questions and rigorous reference answers with defensible scientific reasoning; Interpret experiments, datasets, figures, sequences, structures, and other biological evidence; Validate biological claims, calculations, assumptions, and conclusions.
We are looking for experienced Software Engineers with a strong background in developing and operating large-scale production systems. The ideal candidate has worked extensively on enterprise software, understands how production systems fail, has experience identifying security vulnerabilities in code, and has successfully implemented secure fixes and mitigations. Main tasks listed: Design and build realistic coding-agent benchmark tasks using production-like repositories, tests, configs, documentation, and runtime scenarios; Create benign engineering tasks such as bug fixes, feature additions, CI repairs, config migrations, integration updates, and runtime-state fixes; Define clear utility requirements to verify that the coding agent completes the requested task correctly; Define safety/alignment requirements to ensure the agent preserves system constraints, developer intent, data integrity, privacy, permissions, and oversight mechanisms.