We are looking for a Data Scientist to join our team, focusing on moving AI beyond the experimental phase and into production-scale manufacturing settings.
If you enjoy the challenge of building end-to-end ML solutions and seeing your models drive real-world industrial impact.
You will support the development of AI/ML solutions tailored for Solar Manufacturing, working across a diverse technical landscape:
Computer Vision: Implementing robust models for real-time industrial inspection and quality control.
Time-Series Analysis: Developing forecasting and anomaly detection models for manufacturing telemetry.
Generative AI: Building practical, LLM-powered tools and Retrieval-Augmented Generation (RAG) pipelines to enhance operational efficiency.
What Were Looking For:
A "Deployment-First" Mentality: Experience or a strong interest in MLOps and the practicalities of deploying and monitoring models in a production setting.
Technical Foundations: Solid proficiency in Python and hands-on experience with contemporary libraries:
CV & Time-Series: PyTorch, TensorFlow, OpenCV, or Scikit-learn.
Generative AI: Exposure to RAG frameworks (e.g., LangChain, LlamaIndex) and libraries for LLM orchestration and vector databases.
Deployment & Infrastructure: Experience with Docker, containerization, and basic CI/CD pipelines to ensure models are production-ready.
Execution Focus: Your primary goal will be developing stable, scalable solutions that function reliably on the shop floor.
Qualifications: Bachelor’s or Master’s degree in Engineering, Computer Science, or a related quantitative discipline with relevant industry experience.