Senior Perception Engineer

Your Responsibilities

As a Senior Perception Engineer for John Deere Intelligent Solutions Group located in Santa Clara, CA, you will:

• Develop and maintain perception capabilities across the full autonomy stack — working from onboard C++ systems and sensor interfaces up through applied ML models that interpret the environment.
• Develop and maintain key components of the perception pipeline, including data ingestion, labeling, model execution, and downstream interfaces used by planning and controls.
• Diagnose and resolve perception failures using logs and sensor data — reconstructing system behavior when real‑time debugging isn’t possible and driving issues to root cause.
• Implement and optimize C++ modules running on embedded and edge compute platforms, ensuring real‑time performance, robustness, and clean integration with the broader autonomy system.
• Train, evaluate, and deploy applied ML models for detection, segmentation, tracking, and scene understanding — focusing on production reliability rather than research novelty.
• Improve the quality and maintainability of perception codebases by refactoring legacy components, tightening interfaces, and eliminating technical debt.
• Collaborate closely with robotics, systems, and platform teams to ensure perception outputs meet system‑level requirements and integrate cleanly across boundaries.
• Contribute to team engineering culture through thoughtful code reviews, design discussions, and sharing best practices in C++, ML, and systems debugging.
• Drive clarity in ambiguous problem spaces by breaking down perception issues into actionable engineering tasks and proposing pragmatic solutions. 

VISA Sponsorship is NOT available for this position

What Skills You Need

• 3 or more years of professional software engineering experience, including substantial work in modern C++.
• Hands‑on experience with applied machine learning for perception — training, evaluating, and deploying models using frameworks such as PyTorch or TensorFlow.
• Strong debugging skills, especially in log‑driven environments where issues span multiple processes, sensors, or system layers.
• Experience working with sensor data (camera, LiDAR, radar) and building or maintaining perception pipelines.
• Ability to work effectively across system boundaries — from onboard compute and middleware to cloud‑based data workflows.
• Demonstrated ability to deliver high‑quality, maintainable code and collaborate effectively within a multidisciplinary engineering team. 

What Makes You Stand Out

• Experience with ROS 2 (nodes, lifecycle, launch, parameters, QoS) and its build ecosystem.
• Experience deploying ML models to embedded platforms (Jetson, ARM, x86) and optimizing for latency, memory, or power constraints.
• Background in classical computer vision, sensor fusion, or tracking algorithms.
• Experience with static analysis and code quality tools (clang‑tidy, ASAN/TSAN/UBSAN).
• Experience with simulation environments, synthetic data generation, or system‑level testing frameworks.
• Domain experience in agricultural, mining, construction, or other off‑highway autonomous systems. 
• Solid understanding of Linux development, build systems (CMake, Bazel, or colcon), and containerized workflows (Docker).
• Familiarity with concurrency, performance constraints, and real‑time considerations in robotics or embedded systems.

Education

Ideally, you will have a degree or equivalent related work experience in the following:

• Bachelor’s degree in Computer Science, Electrical Engineering, Robotics, or a related technical field required.
• Master’s degree in Computer Science, Electrical Engineering, Robotics, or a related technical field preferred.
• Equivalent professional experience will be considered in lieu of a formal degree.
• Coursework or demonstrated expertise in perception, machine learning, or robotics software architecture is a plus.