At a Glance
- Tasks: Create cutting-edge datasets and evaluate AI-generated code for efficiency and reliability.
- Company: Join Turing, a leading research accelerator for frontier AI labs.
- Benefits: Flexible hours, remote work, and potential for contract extensions.
- Other info: Engage in a dynamic environment with opportunities for growth.
- Why this job: Make an impact in AI by collaborating with top researchers and engineers.
- Qualifications: 3+ years of software engineering experience, strong Python and JavaScript skills.
The predicted salary is between 60000 - 80000 € per year.
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 by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialise in software engineering, logical reasoning, STEM, multilinguality, multimodality, and agents; and 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 built production systems at companies like Google, Microsoft, Apple, Amazon, Meta, or similar high-scale engineering organisations. We especially welcome graduates from leading programmes 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 across the full stack — in Python for backend and ML workflows, and JavaScript (React, Node.js) for frontend and API layers, alongside C/C++, Java, Rust, and Go. 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 across both Python and JavaScript (React, Node.js), with additional work in C/C++, Java, Rust, and Go.
- Evaluate and refine AI-generated code across backend and frontend contexts to ensure that it is efficient, scalable, and reliable.
- Collaborate with cross-functional teams to enhance AI-driven coding solutions against industry performance benchmarks.
- Build agents that can verify the quality of the code and identify error patterns across full-stack applications.
- 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 building full-stack applications using Python and JavaScript (React, Node.js), with the ability to work across backend and frontend codebases.
- Experience 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. Note: As part of assessments you will go through an AI video interview. After applying, you will receive an email with a login link. Please use that link to access the portal and complete your profile.
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Remote Senior Python Engineer – LLM Evaluation (US-based) in Ashton-under-Lyne employer: Turing
Turing is an exceptional employer that fosters a dynamic and innovative work culture, perfect for Senior Python Engineers looking to make a significant impact in the AI field. With flexible engagement options and opportunities for collaboration with top-tier researchers, employees can expect to grow their skills while contributing to cutting-edge projects in a supportive environment. Located in the vibrant tech hub of San Francisco, Turing offers a unique chance to be at the forefront of AI advancements, making it an attractive choice for those seeking meaningful and rewarding employment.
StudySmarter Expert Advice🤫
We think this is how you could land Remote Senior Python Engineer – LLM Evaluation (US-based) in Ashton-under-Lyne
✨Tip Number 1
Get your networking game on! Reach out to folks in the industry, especially those who work at companies like Google or Amazon. A friendly chat can lead to insider info about job openings and even referrals.
✨Tip Number 2
Prepare for that AI video interview! Brush up on your Python and JavaScript skills, and be ready to showcase your problem-solving abilities. Practising common coding challenges can really help you stand out.
✨Tip Number 3
Show off your projects! Whether it's a GitHub repo or a personal website, having a portfolio of your work can make a huge difference. It gives potential employers a taste of what you can do with code.
✨Tip Number 4
Don't forget to apply through our website! It's the best way to ensure your application gets seen. Plus, we love seeing candidates who take the initiative to connect directly with us.
We think you need these skills to ace Remote Senior Python Engineer – LLM Evaluation (US-based) in Ashton-under-Lyne
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter for the role. Highlight your experience with Python and JavaScript, and any relevant projects you've worked on. We want to see how your skills align with what we're looking for!
Showcase Your Projects:Include links to your GitHub or any other portfolio showcasing your work. We love seeing real examples of your coding prowess, especially in full-stack applications. It gives us a better idea of what you can bring to the table!
Be Clear and Concise:When writing your application, keep it straightforward. Use clear language and structure your thoughts well. We appreciate good communication skills, so make sure your written application reflects that!
Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way to ensure we receive all your details correctly. Plus, it makes the process smoother for both you and us!
How to prepare for a job interview at Turing
✨Know Your Tech Stack
Make sure you’re well-versed in Python and JavaScript, especially React and Node.js. Brush up on your knowledge of C/C++, Java, Rust, and Go too, as they might come up during the interview. Being able to discuss your experience with these languages confidently will show that you're a strong candidate.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific examples where you've built scalable, production-grade software. Think about challenges you faced and how you overcame them. This will demonstrate your ability to think critically and adapt, which is crucial for the role.
✨Communicate Clearly
Since excellent communication skills are a must, practice articulating your thoughts clearly and concisely. You might be asked to explain complex concepts or your evaluation rationale, so being able to convey your ideas effectively will set you apart.
✨Familiarise Yourself with AI Concepts
Given the focus on AI model training and evaluation, it’s beneficial to brush up on relevant AI concepts and methodologies. Understanding how large language models work and their applications will help you engage more meaningfully during discussions.
