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: Collaborative environment with opportunities to work on innovative AI projects.
- Why this job: Make an impact in AI development while working with top-tier engineers.
- Qualifications: 3+ years of software engineering experience, strong Python skills, and full-stack application knowledge.
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 top computer science programmes such as Stanford, MIT, Carnegie Mellon, UC Berkeley, Georgia Tech, 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 — with a primary focus on Python across backend services, data pipelines, and ML infrastructure, alongside JavaScript (including ReactJS), 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 — primarily in Python, with additional work in JavaScript (including ReactJS), C/C++, Java, Rust, and Go.
- Evaluate and refine AI-generated code 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 and automated verification tools in Python that can verify the quality of code and identify error patterns.
- 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 Python with deep knowledge of frameworks, tooling, and best practices for building production-grade software.
- Experience building full-stack applications and deploying scalable 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 Software Engineer in Leigh employer: Turing
Turing is an exceptional employer for Senior Software Engineers, offering a dynamic work culture that fosters innovation and collaboration in the cutting-edge field of AI. With flexible engagement options and opportunities to work alongside top-tier researchers, employees can expect significant growth in their technical skills while contributing to impactful projects that shape the future of AI technology. Located in the vibrant tech hub of San Francisco, Turing provides a stimulating environment that encourages creativity and professional development.
StudySmarter Expert Advice🤫
We think this is how you could land Remote Senior Software Engineer in Leigh
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at tech meetups. We all know that sometimes it’s not just what you know, but who you know that can help you land that dream job.
✨Tip Number 2
Prepare for those interviews! Brush up on your coding skills and be ready to showcase your problem-solving abilities. We recommend doing mock interviews with friends or using platforms that simulate real interview scenarios.
✨Tip Number 3
Show off your projects! Whether it's on GitHub or your personal website, having a portfolio of your work can really set you apart. We love seeing what you've built and how you think through problems.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we’re always on the lookout for talented engineers like you to join our team!
We think you need these skills to ace Remote Senior Software Engineer in Leigh
Some tips for your application 🫡
Show Off Your Skills:When you're writing your application, make sure to highlight your experience with Python and any other languages mentioned in the job description. We want to see how you've built production systems and tackled challenges in your previous roles.
Tailor Your Application:Don't just send a generic application! Take the time to tailor your CV and cover letter to reflect the specific skills and experiences that match what we're looking for. This shows us you’re genuinely interested in the role and understand what it entails.
Be Clear and Concise:We appreciate clear communication, so keep your application straightforward and to the point. Use bullet points where possible to make it easy for us to read through your qualifications and achievements.
Apply Through Our Website:Make sure to apply through our website for the best chance of getting noticed. It streamlines the process for us and ensures your application is in the right hands!
How to prepare for a job interview at Turing
✨Know Your Tech Stack
Make sure you’re well-versed in Python and the other languages mentioned, like JavaScript, C/C++, and Rust. Brush up on frameworks and best practices for building production-grade software, as you’ll likely be asked to discuss your experience with these technologies.
✨Showcase Your Problem-Solving Skills
Prepare to demonstrate your ability to evaluate and refine AI-generated code. Think of examples where you've improved code efficiency or scalability in past projects. Be ready to explain your thought process clearly, as communication is key in this role.
✨Familiarise Yourself with AI Concepts
Since the role involves working closely with AI models, it’s a good idea to brush up on AI concepts and how they relate to software engineering. Understand the basics of model training and evaluation, and be prepared to discuss how you can contribute to these initiatives.
✨Practice Your Communication Skills
Given the emphasis on clear, structured evaluation rationales, practice articulating your thoughts on technical topics. You might want to do mock interviews with friends or use platforms that focus on technical interviews to get comfortable explaining complex ideas simply.
