Applied Machine Learning Engineer - Terra Quantum

Key Responsibilities

• Design, implement, and deliver complete ML pipelines for industrial use‑cases, from data ingestion and feature engineering to model training and production deployment.
• Apply state‑of‑the‑art techniques in time‑series forecasting, optimization, computer vision, natural language processing, and generative AI to solve client problems.
• Collaborate with domain experts and software engineers to integrate ML models into scalable, robust solutions.
• Perform model selection, hyperparameter optimization, and rigorous validation to ensure performance and reliability.
• Document methodologies, create reproducible codebases, and mentor junior team members on best practices.

Requirements

• Strong proficiency in Python and ML libraries such as TensorFlow, PyTorch, and scikit‑learn.
• Hands‑on experience building and deploying models for time‑series, computer vision, NLP, or generative AI tasks.
• Solid understanding of data preprocessing, feature engineering, and model evaluation techniques.
• Experience with cloud platforms (e.g., AWS, Azure) and containerization tools for productionizing models.
• Excellent problem‑solving skills and ability to work autonomously in a fast‑paced research environment.