Caterpillar
Industrial · Autonomous mining trucks
- HQ
- Irving, US
- Founded
- 1925
- Funding
- Public (CAT)
- Website
- caterpillar.com
Caterpillar currently has 28 active job listings related to artificial intelligence. The majority of these roles, 54%, are focused on agents, with serving infrastructure and data each accounting for 18% of the listings. The dominant function for these positions is Engineering. In the last 30 days, Caterpillar has posted 40 new AI roles, representing a significant increase of 1233% compared to the previous 30-day period.
Currently tracking 22 active AI roles, down 12% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $113k–$240k (avg $180k).
Industrial · Autonomous mining trucks
Caterpillar currently has 45 active AI-related roles in our index. The most common open titles are: Data Scientist (3), Manager, Product Management (Platform) (3), Autonomy Development Engineer (2), Autonomy Engineering Development Specialist (2), Senior Autonomy Engineer (2). Most positions are in Engineering and Product.
Caterpillar's active AI hiring is concentrated in: agents (60%), data (27%), serving infrastructure (9%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Caterpillar is hiring AI talent in: United States (29 roles), China (2 roles), Belgium (2 roles).
Job postings at Caterpillar most frequently reference: agent orchestration, model serving, llm observability, inference infra, evals.
In the past 30 days, Caterpillar has posted 75 new AI-related roles. That is a +53% change versus the prior 30 days (49 → 75).
| Title | Stage | AI score |
|---|---|---|
| Back Office Engineering Manager Engineering Manager for Caterpillar's autonomous mining systems back-office platform. Responsibilities include leading a team in the development and architectural design of the platform, covering areas like autonomous driving operations statistics and management, dispatch systems and algorithm development, map creation and management, digital twins, data analysis and efficiency optimization, user interface, network integration, server architecture, data storage and algorithms, machine learning and artificial intelligence applications, and remote control switching. The role requires strong experience in back-office system development, team management, and technical skills in distributed systems, algorithms, and ML frameworks. | AgentData | 7 |
| Planning Engineer Planning Engineer role at Caterpillar focused on path and behavior planning for autonomous mining vehicles in unstructured environments. Responsibilities include task-level route planning, trajectory and speed planning considering vehicle dynamics and terrain, and perception-based behavior planning. Requires strong C++/Python skills, familiarity with Linux and ROS/ROS2, and knowledge of ML/DL/RL applications in planning. Experience in autonomous driving planning and decision-making is essential, with mining/construction scene experience being a plus. |
| Agent |
| 7 |
| Perception deployment engineer This role focuses on deploying, optimizing, and validating deep learning perception models on embedded platforms for autonomous mining vehicles. It involves using tools like TensorRT and CUDA for inference acceleration, performance analysis, and system-level engineering in a Linux Embedded environment. Collaboration with algorithm, fusion, system, and hardware teams is crucial for integration and evolution, as well as problem-solving during full-process debugging and testing. | Serve | 7 |
| Autonomy Simulation Engineer The role is responsible for the design and development of the simulation architecture for mine autonomous driving systems, covering backend control system simulation, autonomous vehicle simulation, subsystem simulation, and simulation and testing of autonomous driving algorithms. The goal is to achieve efficient verification and iteration in a virtual environment, reduce on-site testing risks, and improve development efficiency. Key responsibilities include building a simulation platform for multi-vehicle, multi-scenario collaborative testing, simulating backend logic, developing vehicle dynamics and sensor models, simulating core algorithms like path planning and obstacle avoidance, and developing test scenarios. Experience with simulation systems (CARLA/AirSim/Isaac Sim), ROS, C++, Python, and multi-agent simulation frameworks is required. Familiarity with machine learning/deep learning, especially data-driven or reinforcement learning methods in simulation, is a plus. | Agent | 7 |