Build challenging AI coding tasks from familiar repositories, including task briefs, correct solutions, grading checks, stress tests, and model evaluations. Revise tasks through quality review and produce work suitable for training and assessing AI coding models. Requires at least 10 hours weekly and strong software engineering, testing, repository, and AI coding tool experience.
We're looking for experienced software engineers to build AI coding tasks from a codebase they know well. US$1,000 per task, and you can do as many tasks as you want.
You turn a real change from a repository you know into a task that today's best AI coding models struggle with: hard for the models, but fair for a skilled engineer. Your tasks are used to measure and train AI coding models.
Remote, any location. US$1,000 per task that passes review. Minimum of one task a week, about 10 hours a week.
How it works
- Apply. Complete a short screener interview and upload your resume.
- Propose. Once you're selected, pick a change from a repository you know and submit a short proposal. We approve it or suggest a better candidate.
- Build. In our platform, set up the repository as it was before the change, then write the brief, the correct solution and the grading checks.
- Stress-test. Try lazy, incorrect and shortcut solutions and make sure your checks catch them.
- Model testing. Run your task against leading AI models until strong models often fail but a skilled engineer can clearly solve it.
- Review. A reviewer checks your task and you revise it. Most tasks take more than one round.
- Next task. Once your task is accepted, start another.
Requirements
- 2+ years of professional software engineering
- Code merged into a public open-source repository, ideally one you know well. A private codebase you own may also qualify (not employer or client code)
- Strong in at least one of Python, TypeScript, Go, Rust, Java or C++
- Solid with Docker, Linux, Git and automated testing
- Regular use of an AI coding tool
- Experience writing tests, rubrics or evaluation criteria, ideally for AI models
- You can explain a change clearly and concisely, in your own words
- At least 10 hours a week, starting now
- A secure personal or work computer (no public or shared machines)
Nice to have
- Deep expertise in one area, such as databases, compilers, distributed systems, security or infrastructure
- Experience building agent tasks or RL environments
Terms
- US$1,000 for each task that passes our quality review, paid directly to you
- Once your proposal is qualified, you sign Askable's contract and accept its terms
- The work is used for AI training. The change and your solution must be your own, and you must be free to license them to us
- Don't publish the work anywhere: no public pull request or public fork
Apply at https://www.askable.com/experts/roles/senior-software-engineer
Similar Jobs
Cloud • Information Technology • Productivity • Security • Software • App development • Automation
The Account Executive will drive enterprise sales for financial services customers across the Americas. The role is remote and involves managing customer relationships and pursuing business opportunities. Specific responsibilities and qualifications are not provided in the available job description.
Consumer Web • Healthtech • Professional Services • Social Impact • Software
Leads and coaches a team of 6–7 recruiters supporting Provider Sales and Care Partnerships. Owns recruiting strategy, complex requisitions, sourcing, process design, pipeline health, offer closing, recruiting metrics, stakeholder partnerships, interviewer training, and process improvement. Serves as an executive-facing talent advisor while driving consistent, inclusive, data-informed hiring practices in a high-growth environment.
Artificial Intelligence • Cloud • Sales • Security • Software • Cybersecurity • Data Privacy
Executive leader responsible for enterprise technology, business applications, and agentic AI transformation. Leads Financial Systems, People Technology, and an Enterprise AI Lab; architects secure AI infrastructure using LLM gateways, MCP, tool-calling, and RAG; partners with business leaders to automate cross-system workflows; establishes governance, operating models, engineering practices, roadmaps, metrics, and enterprise-scale AI deployment.
Top Skills:
Aws BedrockBigQueryClaude CodeCursorGcp Vertex AiLlmsModel Context Protocol (Mcp)NetSuiteNumpyPandasPythonPyTorchRetrieval-Augmented Generation (Rag)SalesforceScikit-LearnSnowflakeWorkday
What you need to know about the NYC Tech Scene
As the undisputed financial capital of the world, New York City is an epicenter of startup funding activity. The city has a thriving fintech scene and is a major player in verticals ranging from AI to biotech, cybersecurity and digital media. It also has universities like NYU, Columbia and Cornell Tech attracting students and researchers from across the globe, providing the ecosystem with a constant influx of world-class talent. And its East Coast location and three international airports make it a perfect spot for European companies establishing a foothold in the United States.
Key Facts About NYC Tech
- Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
- Key Industries: Artificial intelligence, Fintech
- Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
- Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory
