AI/ML Engineer - Time Series Robotics

Role overview

Responsibilities

• check_circle Design and implement ML models for time-series sensor data (e.g., currents, torques, IMUs, joint states, vehicle signals, cameras, GPS).
• check_circle Build and maintain data pipelines for collection, preprocessing, feature extraction, and labeling.
• check_circle Prototype algorithms in Python (e.g., PyTorch, TensorFlow) and collaborate with embedded engineers to create deployable, resource-efficient models.
• check_circle Evaluate model performance using appropriate metrics; iterate to improve robustness and generalization across platforms and use cases.
• check_circle Work with robotics and vehicle engineers to understand requirements and convert them into concrete ML problems and model specifications.
• check_circle Support data visualization, dashboards, and tools for internal users to interpret model outputs and system behavior.
• check_circle Document models, experiments, datasets, and results to ensure reproducibility and traceability.

Basic qualifications

• Bachelor’s, Master’s, or PhD in Computer Science, Electrical Engineering, Applied Mathematics, or a related field.
• Hands-on experience with machine learning for time-series or sensor data.
• Strong proficiency in Python and ML frameworks such as PyTorch or TensorFlow.
• Familiarity with data science tools and workflows (NumPy, Pandas, Jupyter, etc.).
• Ability to work in a cross-functional team and communicate technical concepts clearly.

Preferred qualifications

• Experience with embedded / edge AI or model compression and optimization techniques.
• Familiarity with control systems, robotics, or vehicle dynamics.
• Experience with MLOps tools (experiment tracking, model versioning, CI/CD for ML).
• Prior work in a product or R&D environment with multi-disciplinary teams.