The company is building a next-generation AI-enabled assistant for hardware designers that blends machine learning, 3D geometry, simulation, and constraint reasoning to guide engineers through design exploration. They are looking for a Data Engineer to build scalable systems adept at working with application data to support the growth of their models, applications, and feature suite.
Requirements
- Experience with data transformation and optimization techniques for scaling applications and ML systems
- Worked in Python to transform data into pipelines using Postgres, Alembic, and SQLAlchemy
- Strong grasp of SQL and comfortable with optimizing SQL for production
- Knowledge of orchestrators like Airflow, Dagster, and Temporal
- Experience working with agentic systems
- Experience working in on prem containerized deployments
Responsibilities
- build systems that are scalable and are adept at working with application data
- build out our systems so they can grow with our models, applications and feature suite
- become an expert in our data schemas, data transforms, and pipelines that provide pathways to new features and allow our customers to efficiently use our application
- facilitate ML models
- data transformation and optimization techniques for scaling applications and ML systems
- transform data into pipelines using Postgres, Alembic, and SQLAlchemy
- optimizing SQL for production
Other
- 5+ years of experience in Data engineering, with some of this time working in systems that facilitate ML models
- Comfortable working in startup environment with comfort understanding dataflows across the stack
- You’ll be part of a team that cares deeply about real-world impact, clean abstractions, and usable AI tools for human designers.
- You’ll have autonomy to pursue principled approaches, backed by a strong foundation in AI and design engineering.
