Top AI & Machine Learning Jobs

Build data products and automations by translating business questions into technical requirements, assessing data and process gaps, and developing analytics solutions. Create actionable Power BI dashboards, support cross-functional decision-making, and guide junior data scientists and citizen developers. The role requires strong skills in Python, SQL, data analytics, AI, automation, data modeling, business requirements analysis, communication, and project management.

Defines enterprise data and AI infrastructure architecture for physical AI and autonomous systems. Designs data domains, canonical models, data products, GPU platforms, distributed training environments, simulation pipelines, MLOps workflows, and edge deployment architectures. Leads technology evaluation, technical standards, implementation planning, and cross-functional delivery across cloud and on-premises environments. Enables engineers and data scientists to develop, validate, and deploy scalable AI models for autonomous construction equipment.

Leads a multidisciplinary data science and AI pod focused on AI-assisted engineering tools, adoption, analytics, and productivity measurement. Develops technical plans, guides deployment and troubleshooting, supports Agile product ownership, reports actionable insights, and mentors data science, machine learning, GenAI, and software engineering professionals. Partners with users, product owners, architects, engineers, and business stakeholders to shape scalable enterprise AI enablement services while applying responsible AI principles.

Build data products and analytical models for Caterpillar’s product support teams. Responsibilities include large-scale data collection, processing, mining, statistical modeling, machine learning, NLP, text analytics, requirements analysis, and data visualization. The role translates complex insights into actionable recommendations and system requirements while collaborating with engineers, dealers, leaders, and internal customers. Work is onsite five days per week in Peoria, Illinois, with approximately 10% travel.

Owns the technical vision, architecture, and roadmap for Caterpillar’s high-fidelity simulation platform supporting physical AI and autonomous construction and mining machines. Defines physics, sensor, rendering, scenario, execution, and training abstractions; establishes fidelity, determinism, performance, and developer experience standards; and leads sim-to-real validation. Collaborates across simulation, digital twin, AI, autonomy, perception, controls, and machine engineering teams while scaling deterministic simulation across GPU clusters and cloud infrastructure.

Leads statistical validation for safety-related AI products across design, deployment, and operation. Defines safety metrics, acceptance criteria, and confidence levels; designs experiments and analyzes simulations, field data, rare events, uncertainty, distribution shifts, and failure modes. Applies Bayesian inference, reliability, survival, causal, and uncertainty analysis methods. Collaborates with engineering teams on safety cases, supports post-deployment monitoring and revalidation, and mentors technical staff.

Lead and develop a software engineering team building cloud-native AI agents, assistants, orchestration frameworks, tooling, and observability solutions. Own technical strategy, architecture, delivery, reliability, security, scalability, operational excellence, and production support. Partner with product, data science, architecture, and business teams while managing releases, resources, risks, and multiple initiatives. Coach engineers, improve engineering practices, and ensure responsible AI and governance compliance.

Develops and maintains data-driven solutions for aftermarket parts inventory planning, including production processes, Power BI dashboards, data architecture, predictive modeling, simulations, and advanced analytics. Performs inventory analysis, supports business intelligence and ad hoc requests, optimizes analytical programs, and evaluates generative AI opportunities. Partners with technical and business stakeholders to deliver actionable insights and continuous process improvements. The role is fully onsite in Morton, Illinois and requires up to 10% domestic travel.

Lead analytics and applied AI initiatives using statistical and machine learning methods to solve business challenges and support sales and services growth. Partner with stakeholders to develop insights, models, and scalable digital solutions; mentor data scientists; research emerging techniques; and communicate findings to technical and non-technical audiences.

Designs enterprise agentic AI architectures, including orchestration layers, tool integrations, retrieval patterns, testing, and infrastructure. Leads evaluation and deployment of emerging AI technologies, translates business requirements into scalable solutions, and advises cross-functional teams on architecture decisions. The role emphasizes multi-agent systems, LLMs, RAG, cloud AI platforms, MLOps, LLMOps, enterprise integration, and production AI systems.