Data Engineer AI ML

Data Engineer AI ML at micro1

About Us:

micro1 is a data engine that helps AI labs train foundational models and enterprises build AI agents. We provide frontier evaluations and reinforcement learning environments used to improve LLM capabilities, as well as contextual evaluations used to monitor and improve AI agents in enterprise settings. Our data engine includes an AI recruiter agent that sources and vets domain experts, a data platform that enables rapid production of high-quality training data, and a pipeline performance system that ensures both quality and velocity.

The Role:

We are looking for a Data Engineer to support data infrastructure and experimentation in an AI research environment. In this role, you will build reliable data pipelines, explore datasets, and help transform raw data into structured formats that enable research and model development.

Key Responsibilities

• Design, build, and maintain scalable data pipelines to ingest, process, and transform data from multiple sources.
• Collaborate with AI researchers and data scientists to structure and prepare datasets for experimentation and model training.
• Develop and maintain data models, schemas, and storage systems optimized for large-scale datasets.
• Write efficient SQL queries and Python scripts to extract, transform, and analyze data.
• Ensure data quality, integrity, and reliability across data pipelines and storage layers.
• Implement data validation, monitoring, and automation workflows that support iterative research cycles.

Required Skills and Qualifications

• Strong proficiency in Python and SQL.
• Experience designing and maintaining ETL / ELT pipelines.
• Solid experience with data manipulation libraries such as Pandas and NumPy.
• Experience working with structured and semi-structured datasets.
• Familiarity with relational databases such as PostgreSQL or MySQL.
• Strong analytical thinking and ability to work in collaborative research-driven environments.
• Excellent written and verbal communication skills.

Nice to Have

• Exposure to AI/ML workflows or research environments.
• Experience with data visualization tools such as Matplotlib, Seaborn, or Plotly.
• Familiarity with LLM-related data workflows (datasets for training, evaluation, or prompt experimentation).

Key skills/competency

• Data Engineering
• Python
• SQL
• ETL/ELT
• Data Pipelines
• Data Modeling
• Data Analysis
• AI/ML
• Pandas
• NumPy