Surge AIData Scientist
AI in this role
About Us
Our mission is to raise AGI with the richness of human intelligence — curious, witty, imaginative, and full of unexpected brilliance.
Surge was founded by engineers and researchers who dreamed of building the next generation AI. We're building a platform that powers the most powerful models in the world in partnership with companies like OpenAI, Anthropic, Meta, and Google.
At Surge, we believe the path to AGI isn't just about scaling compute—it's about embracing the unlimited ceiling of human intelligence and creativity in the data that shapes these systems. Our platform combines elite human expertise with cutting-edge tools for scalable oversight, from building rich RL environments to conducting rigorous evaluations that go beyond benchmarks. We've run a profitable business from day one without raising venture funding.
The Role
As a Data Scientist, you’ll partner directly with leading AI labs to shape how their models are trained, evaluated, and improved. You’ll embed with research teams to understand their performance bottlenecks, design targeted data collection strategies, and analyze experimental results to drive model progress.
This role is ideal for someone who thrives on impact and iteration — someone who loves digging into ambiguous problems, rapidly prototyping data workflows, and turning messy real-world feedback into actionable insight. Your work will live at the heart of frontier AI development, influencing how the most advanced models learn and align with human values.
What We’re Looking for
Passion for Data Analysis - Analyzing data and iterating on collection methods to improve model performance
Curiosity About LLMs - You've dug into how large language models work — not just as a user, but at a conceptual level. You can speak confidently about fine-tuning, RLHF, evaluation, and model behavior, even if you haven't built one from scratch.
Love of Customer Collaboration - You're energized by working directly with AI researchers and technical customers. You can translate complex model behavior into clear insights, ask good questions, and earn trust in a room full of experts
Python Proficiency - You're comfortable writing Python to analyze data, build pipelines, and prototype workflows. You don't need to be a software engineer, but code is one of your primary tools
What You'll Do
Design data collection workflows optimized for particular model needs
Implement quality controls to reduce biases and ensure model safety
Run experiments to make leading models more insightful, compelling, safe, and human aligned
How we rate this
Data Scientist at Surge AI rates 93 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- Walk me through fine-tuning a model: what data did you use, and how did you check the result?
- Walk me through how you've used OpenAI in your day-to-day work.
- What are the limits of Anthropic that you've run into, and how did you work around them?
- How would you decide a model or AI system is ready to ship?
- Tell me about a time a model underperformed in production. How did you find out, and what did you change?
Adapt your resume
- List these exact terms on your resume: Fine Tuning, OpenAI, and Anthropic. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.
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