Hiring: SWE Bench – Data Engineer / Data Scientist at Turing (Remote)

Software Engineer (SWE Bench – Data Engineer / Data Science) at Turing

Turing is a Silicon Valley-based “AI-first” tech company that acts as a bridge between global engineering talent and world-class AI labs. This specific SWE Bench role is critical to the evolution of Large Language Models (LLMs). You won’t just be building pipelines; you’ll be creating the benchmarks that define how “smart” the next generation of AI becomes.

🟢 Role Overview & Impact

In this role, you aren’t just an engineer; you are a researcher. You will be designing the “exams” that AI models take to prove they can handle real-world data science tasks.

• Benchmark Evaluation: Working on SWE Bench style tasks—evaluating if AI can fix real bugs, navigate complex codebases, and perform data science workflows autonomously.

• The “Data” Focus: You will design pipelines to feed production-like datasets into evaluation loops, ensuring that transformations are reproducible and high-quality.

• AI Training: Your day-to-day involves writing Python code to simulate real-world data science problems, helping LLMs improve their coding and STEM reasoning.

📊 Compensation & Offer Details (2026 Benchmarks)

Based on the current 2026 data for Turing contractors in India:

🎯 Key Requirements to Highlight

• 3+ Years Experience: A solid foundation in Data Engineering or Data Science.

• Python Mastery: You must be able to write “production-grade” Python—clean, documented, and maintainable.

• The “Reasoning” Mindset: You need to understand how to break down complex algorithmic problems. Turing values engineers who can think like researchers.

• Communication: Excellent English is non-negotiable since you’ll be collaborating with San Francisco-based researchers.

   

💡 Strategy for Success with Turing

Turing’s vetting process is famously rigorous. To stand out:

1. The Turing Test: Prepare for an algorithmic coding challenge and a specialized Data Engineering test on their platform.

2. Highlight your “Dual Skills”: Since the role combines SWE, Data Engineering, and Data Science, mention projects where you had to navigate a complex codebase to fix a data pipeline issue.

3. Time Zone Readiness: Be prepared to work late evenings or early mornings in India to meet the PST overlaprequirement.