Engineer -AI/ML -Time Series & Robotics

Key Responsibilities

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

Required Qualifications

• Bachelor’s, Master’s, or PhD in Computer Science, Electrical Engineering, Applied Mathematics, or a related field.
• Experience with embedded / edge AI or model compression and optimization techniques.
• Hands-on experience with machine learning for time-series or sensor data.
• Strong proficiency in C++ and ML frameworks.
• Experience working with real-world noisy data (e.g., automotive, robotics, industrial, IoT).
• 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

• Familiarity with control systems, robotics, or vehicle dynamics.
• Experience with MLOps tools (experiment tracking, model versioning, CI/CD for ML).
• Experience with ROS or other multimodal sensor data frameworks.
• Prior work in a product or R&D environment with multi-disciplinary teams.