[Hiring] Research Engineer Curator @Applabsystems

Role Description

We are looking for a Research Engineer (RE) Curator to design, implement, and review complex, multi-step research tasks that simulate real-world engineering challenges. The ideal candidate should have a strong background in research, data analysis, Python programming, and AI/ML, with the ability to work independently and deliver high-quality technical work.

Key Responsibilities

• Design and review complex research and engineering tasks.
• Write, debug, and optimize Python scripts.
• Conduct machine learning experiments and analyze results.
• Work with Large Language Models (LLMs) and AI coding assistants.
• Perform data analysis, data cleaning, statistical correlation, and result interpretation.
• Use Jupyter Notebook or Google Colab for experimentation and reporting.
• Follow software development best practices using Git and modern IDEs.
• Create clear documentation and technical reports.
• Design test cases, perform debugging, and ensure software quality.
• Collaborate with research teams to improve AI model evaluation and experimentation.

Qualifications

• MSc or PhD in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering, Mathematics, Statistics, or another STEM field.
• OR equivalent practical experience in a research-focused role involving coding and data analysis.
• Minimum 1+ year of experience in Research Engineering, AI/ML, Data Science, or a related research role.

Required Skills

• Strong Python programming and debugging skills.
• Experience with Git, version control, and software development workflows.
• Understanding of Machine Learning concepts and model evaluation.
• Knowledge of Large Language Models (LLMs) and AI-assisted coding tools.
• Experience with data analysis, statistics, and experimental design.
• Proficiency in Jupyter Notebook or Google Colab.
• Strong analytical thinking and problem-solving skills.
• Excellent written and verbal English communication.

Preferred Skills

• Experience with Reinforcement Learning (RL).
• Test engineering or software quality assurance experience.
• Experience with LLM evaluation or AI model testing.
• Knowledge of LLM Red Teaming or AI Safety.
• Experience working with Research Scientists or research teams.

Tools & Technologies

• Python
• Git
• Jupyter Notebook / Google Colab
• AI Coding Assistants (Gemini, JetBrains AI, GitHub Copilot, etc.)
• Machine Learning Frameworks (TensorFlow, PyTorch, Scikit-learn)
• Data Analysis Libraries (Pandas, NumPy, Matplotlib)