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Caterpillar

Makes heavy machinery, engines and gas turbines

Lead AI Platform Engineer

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeNo salary listedIn-person

About the Job

Requirements

  • A master's degree or higher in computer science, artificial intelligence, automation, mathematics, or a related major is required.
  • At least 6 years of experience in AI, machine learning, or large-scale software systems, including at least 2 years of experience designing the architecture of or technically leading AI platforms or ML systems.
  • Hands-on project delivery experience with LLM, VLM, or VLA, and familiarity with the principles and engineering practice of RAG and Agent frameworks.
  • Familiarity with the AI lifecycle, including data management, distributed training, model evaluation, MLOps or LLMOps, deployment, and monitoring, with in-depth practical experience in multiple stages; experience as a lead or core contributor to building an AI platform from scratch or at scale.
  • Proficiency with deep-learning frameworks such as PyTorch and familiarity with one or more of Kubernetes, MLflow, and Ray.
  • Strong architecture abstraction, technical judgment, and cross-team execution abilities.
  • Good English reading, writing, and communication skills sufficient for technical exchange with global teams.

Responsibilities

  • Develop the AI platform's technical strategy and multi-stage roadmap across ML, VLA, LLM, RAG, and Agent technologies, balancing near-term delivery with long-term evolution.
  • Define the overall AI platform architecture and design standards, align technical approaches for training (data, training, evaluation, and model management) and runtime (vehicle and edge deployment and inference), and establish reference architectures for Agent and RAG capabilities.
  • Abstract common AI capabilities across businesses into reusable platform services, tools, and best practices to reduce duplication and improve development efficiency.
  • Establish model lifecycle governance, including version management, pre-launch evaluation and admission standards, data security and compliance, and compute-resource planning and efficiency; define model delivery specifications between training platforms and vehicle and edge runtimes, including formats, versions, performance baselines, and acceptance criteria.
  • Lead key platform technology selections and solution reviews to ensure scalability and reliability across autonomous-driving solutions.
  • Collaborate with perception, prediction, planning, VLA, dispatch, and vehicle-deployment teams to translate business needs into platform capabilities and drive AI solutions into autonomous machines and operations in field environments such as mines.
  • Participate deeply in the design and implementation of key modules as the platform's technical expert, and improve related teams' AI engineering capabilities through technical sharing and reviews.

Desired Qualifications

  • Experience building AI platforms in autonomous driving, robotics, or industrial domains; experience in off-highway environments such as mining is preferred.
  • Experience deploying inference on vehicles or at the edge using technologies such as TensorRT, ONNX, or Orin.
  • Experience with large-model post-training, including SFT, RLHF or DPO, and parameter-efficient fine-tuning such as LoRA, as well as building evaluation systems.
  • Experience building AI governance, model safety, or compliance systems.

About the Company

Caterpillar

Makes heavy machinery, engines and gas turbines

Caterpillar makes construction and mining machines, diesel and natural gas engines, industrial gas turbines and locomotives for contractors, mines, energy companies and data center builders. It is the world's largest maker of construction and mining equipment, and its yellow Cat bulldozers and excavators work in nearly every country. Customers buy or rent machines through independent Cat dealers, while its engines and turbines generate electricity and push natural gas through pipelines. Caterpillar earns money from equipment sales and from the parts and repairs that dealers supply over a machine's working life. It was formed in 1925 when California's Holt and Best tractor companies merged, and it is based in Irving, Texas.

Company size
10,001+
Company stage
IPO
Headquarters
Irving, TX
Founded
1925

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