Machine Learning Engineer, Intelligent Sensing Technology

What you'll do

• Develop and prototype new camera experiences, architectures, and technologies for the product line.
• Build end-to-end machine learning pipelines from data acquisition and preprocessing through training and deployment.
• Integrate multimodal sensing signals like vision, audio, IMU, and LiDAR with ML models.
• Deploy machine learning models on mobile, wearable, or robotic platforms under edge computing constraints.
• Implement state-of-the-art architectures including transformers, reinforcement learning, and predictive inference.
• Develop physics-based machine learning models, such as physics-informed neural networks or simulation-to-real transfers.
• Communicate technical tradeoffs, risks, and rationales to both technical and non-technical stakeholders.
• Navigate ambiguity and adapt quickly when research directions shift based on new data.

What we're looking for

• Bachelor's degree and at least 3 years of relevant industry experience in machine learning or AI engineering.
• Master's degree or PhD with substantial applied research experience in a relevant area is preferred.
• Familiarity with state-of-the-art architectures including transformers, reinforcement learning, and predictive inference.
• Strong coding skills using modern ML frameworks like PyTorch and proficiency with AI-assisted development tools.
• Proven experience building end-to-end ML pipelines from data acquisition through training, evaluation, and deployment.
• Experience architecting and integrating multimodal sensing systems (vision, audio, IMU, LiDAR) on mobile, wearable, or robotic platforms.
• Familiarity with on-device/edge ML deployment constraints and background in robotics or embedded systems.
• Knowledge of physics-based machine learning, Bayesian reasoning, and cross-disciplinary collaboration across hardware, software, and design.