Title: Planning Engineer IV
Location: Salt Lake City area (Hybrid Position 3 Days Onsite)
Target Start Date : February 2026
Type: Contract-to-Hire (Direct Hire possible)
Pay Rate : $70.00-$81.50/hr ($145-170K)
Overview
Our client, a leader and growing presence in the robotics and autonomous vehicles space, is seeking a senior-level Planning Engineer to design and deploy AI-driven planning and decision-making systems for autonomous robotic platforms. This role focuses on motion planning, decision modeling, and real-time autonomy, bridging AI research and production systems. You will work closely with robotics, controls, and AI teams to embed intelligent planning capabilities into operational autonomous products.
Responsibilities
- Develop and deploy AI-based planning and decision models that drive autonomous robot behavior, path planning, and task execution.
- Integrate planning algorithms with motion planning, control systems (GNC), simulation environments, and robotics platforms.
- Convert AI planning models into production-ready services, APIs, or embedded components.
- Optimize algorithms for real-time performance, low latency, and safety-critical operation.
- Collaborate with AI, robotics, systems, and software teams in both research and product-focused environments.
- Validate planning systems using simulation, hardware-in-the-loop, and field testing.
- Monitor deployed systems and continuously refine models to improve autonomy, reliability, and efficiency.
Requirements
- Bachelor's degree in Computer Science, Robotics, Computer Engineering, or a related technical field.
- 10+ years of engineering experience, including 2-5+ years working with AI/ML systems.
- Strong programming experience with Python (required); C++ and ROS experience highly preferred.
- Hands-on experience with AI/ML frameworks such as PyTorch.
- Proven background in motion planning, decision modeling, pathfinding, or autonomous robotics planning.
- Experience integrating AI solutions into existing autonomy or GNC platforms.
- Ability to work effectively in cross-functional, fast-growing engineering teams spanning research and product delivery.
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