Freelance Research Engineer

Freelance Research Engineer (RE)

Location: Remote

Engagement : Freelance / Part time work

Working hours: 35 hours a  week 

The Research Engineer (RE) Curator will design, implement, and review complex, multi-step ("mid-horizon") agentic tasks that simulate real-world challenges faced by Research Engineers. Each task will require 1-2 days of continuous effort to complete and will span multiple technical skills. 

Targeted Domains & Sub-domains for Sourcing

To identify suitable candidates, sourcing should target the following domains and sub-domains:

A.  Computer Science & Software Engineering (Core)

Sub-domains:

Python Scripting: Proficiency in writing and debugging Python code.

Development Infrastructure: Familiarity with version control systems (Git), Integrated Development Environments (IDEs), and basic software development workflows.

Agentic Coding: Conceptual understanding or experience using AI coding assistants ( Gemini, Jetski) and understanding prompt engineering or agent workflows.

Software Quality: Clean code practices, readability, and basic debugging skills.

B. Machine Learning & Artificial Intelligence (Core)

Sub-domains:

ML Theory & Practice: Foundational understanding of machine learning concepts, model training, and evaluation.

Large Language Models (LLMs): Familiarity with LLM capabilities, limitations, and evaluation techniques.

Reinforcement Learning (RL): Basic understanding (helpful for task design involving reward functions).

ML Experimentation: Experience setting up, running, and analyzing ML experiments.

C. Data Science & Quantitative Analysis (Core)

Sub-domains:

Data Analysis & Analytics: Heavy data analysis skills, including statistical correlation, data cleaning, and interpretation.

Notebook Environments: Proficiency in using Jupyter Notebooks or Google Colab for analysis and reporting.

D. STEM Research & Experimental Methodology (Core)

Sub-domains:

Scientific Method: Strong background in experimental design, hypothesis testing, and rigorous evaluation.

Computational Fields: Experience in STEM fields or Computational Humanities/Social Sciences requiring significant computational work.

E. Quality Assurance & Testing (Preferred / Plus)

Sub-domains:

Test Engineering: Experience designing test cases, quality review processes, and debugging complex systems.

F. AI Safety & Security (Preferred / Plus)

Sub-domains:

LLM Red Teaming: Experience in identifying vulnerabilities, edge cases, or failure modes in LLMs.

Candidate Profile & Qualifications

Must-Haves (Minimum Qualifications)

Education: MSc or PhD in a STEM field, or equivalent practical experience in a research-heavy domain requiring data analysis and coding (e.g., computational sociology/humanities).

Experience: 1+ years of experience in a research or research engineering role.

Technical Skills: Basic Python scripting, familiarity with Git/IDEs.

Language: Fluent in English (written and verbal).

Traits: Perfectionist mindset, high attention to detail, creativity in task design, ability to work independently and handle ambiguity.

Nice-to-Haves (Preferred Qualifications)

Experience working directly with or as a Research Scientist.

Prior experience as a Test Engineer or Quality Reviewer.

Experience in Red Teaming for LLMs.

Objective: Develop a new version of the RE-Bench evaluation benchmark (used for hillclimbing by Code Strike and others) by collecting high-quality, complex, "hard" tasks in a red-teaming setup.

Working Model: Tight feedback loop with researchers, including daily syncs. Curators will have access to internal tools (Jetski, google3 codebase) and unreleased model checkpoints.