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: Earn $300/hr with flexible hours and potential for extension.
- Other info: Collaborative environment with opportunities for growth and innovation.
- Why this job: Make a real impact in AI while working with top-tier engineers.
- Qualifications: 3+ years of software engineering experience and full-stack expertise.
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.
Ideal Background: This role is ideal for engineers who have shipped high-impact products at fast-moving companies like Stripe, Airbnb, Cloudflare, Datadog, Coinbase, or similar high-growth engineering environments. We especially welcome graduates from programs with strong CS foundations such as University of Washington, University of Illinois Urbana-Champaign, UT Austin, University of Michigan, Purdue, 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 Software Engineer ($300/hr.) in Ashton-under-Lyne employer: Turing
Turing is an exceptional employer that fosters a dynamic and innovative work culture, perfect for remote Software Engineers looking to make a significant impact in the AI field. With competitive compensation of $300/hr and flexible engagement options, Turing prioritises employee growth through collaboration with top-tier researchers and exposure to cutting-edge technologies. Working from anywhere in the United States, you'll be part of a forward-thinking team dedicated to transforming AI into proprietary intelligence, ensuring your contributions are both meaningful and rewarding.
StudySmarter Expert Advice🤫
We think this is how you could land Remote Software Engineer ($300/hr.) in Ashton-under-Lyne
✨Tip Number 1
Get your networking game on! Reach out to folks in the industry, especially those who've worked at companies like Stripe or Airbnb. A friendly chat can lead to insider info and maybe even a referral!
✨Tip Number 2
Prepare for that AI video interview! Brush up on your coding 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 on GitHub or your personal website, having a portfolio of your work can make a huge difference. It gives us a glimpse into your coding style and expertise.
✨Tip Number 4
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 Software Engineer ($300/hr.) in Ashton-under-Lyne
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your application to highlight your experience with full-stack development, especially in Python and JavaScript. We want to see how your skills align with the role, so don’t hold back on showcasing relevant projects!
Show Off Your Communication Skills:Since clear communication is key for this role, ensure your written application reflects that. Use structured language and be concise while explaining your past experiences and how they relate to the job. We love a well-organised application!
Highlight Your Impact:When detailing your previous work, focus on the impact you made in your roles. Did you improve efficiency or scalability? Share those achievements! We’re looking for engineers who have shipped high-impact products, so let us know what you’ve accomplished.
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it only takes 15-30 minutes to complete, so why not get started?
How to prepare for a job interview at Turing
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, especially Python and JavaScript (React, Node.js). Brush up on your knowledge of C/C++, Java, Rust, and Go too. Being able to discuss your experience with these languages confidently will show that you're a strong fit for the role.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific examples where you've tackled complex software engineering challenges. Think about how you’ve improved code efficiency or scalability in past projects. This will demonstrate your ability to evaluate and refine AI-generated code effectively.
✨Communicate Clearly
Since excellent communication skills are crucial for this role, practice articulating your thoughts clearly and concisely. You might be asked to explain your rationale behind certain coding decisions, so being structured in your responses will help you stand out.
✨Familiarise Yourself with AI Concepts
Given the focus on AI-driven solutions, it’s beneficial to have a solid understanding of AI concepts and how they relate to software engineering. Be prepared to discuss how you can contribute to AI model training initiatives and enhance coding solutions using AI.
