AI/ML Engineer

About Us

Innovation. Sustainability. Productivity. This is how we are Breaking New Ground in our mission to sustainably advance the noble work of farmers and builders everywhere. With a growing global population and increased demands on resources, our products are instrumental to feeding and sheltering the world.

From developing products that run on alternative power to productivity-enhancing precision tech, we are delivering solutions that benefit people – and they are possible thanks to people like you. If the opportunity to build your skills as part of a collaborative, global team excites you, you’re in the right place.  

Grow a Career. Build a Future!

Be part of this company at the forefront of agriculture and construction, that passionately innovates to drive customer efficiency and success. And we know innovation can’t happen without collaboration. So, everything we do at CNH Industrial is about reaching new heights as one team, always delivering for the good of our customers.

Job Purpose

The AI/ML Engineer – Data Scientist is responsible for designing, developing, and deploying machine learning models, data pipelines, and intelligent AI agents that generate measurable business value across CNH Industrial. This role bridges classical data science with modern generative and agentic AI, enabling autonomous systems to plan, reason, and act on behalf of the business.

The role covers the full lifecycle of AI/ML solutions: from problem framing and data exploration, through model development and MLOps, to the design of multi-step AI agents that integrate with enterprise systems and execute complex tasks with minimal human intervention.

Leveraging a strong foundation in both statistics and software engineering, the senior holder of this role brings the maturity to mentor junior colleagues, contribute to the AI Center of Excellence, and drive responsible AI adoption aligned with CNH’s digital transformation strategy.

Collaboration happens within Agile/DevOps frameworks, using industry-leading MLOps tooling and cloud platforms.

Delivering production ML models for forecasting and optimization will directly reduce inventory costs and improve Supply Chain efficiency across AG and CE segments.

Agentic AI workflows will automate complex, multi-step manual processes, compressing cycle times and freeing human capacity for higher-value work.

Responsible, well-documented AI solutions will strengthen CNH’s data governance posture and accelerate enterprise adoption of AI at scale.

Key Responsibilities

• Design, build, and deploy end-to-end ML/AI solutions for key business use cases including demand forecasting, anomaly detection, predictive maintenance, NLP, and process optimization.
• Develop and maintain robust data pipelines for feature engineering, model training, evaluation, and production inference, using platforms such as Databricks and Azure ML.
• Design and implement agentic AI systems: autonomous agents capable of multi-step reasoning, tool use, memory, and goal-directed behavior using frameworks such as the Anthropic Claude Agent SDK, LangChain, LangGraph, AutoGen, or equivalent.
• Integrate AI agents with enterprise tools, databases, APIs, and services via MCP (Model Context Protocol) servers, function calling, and REST interfaces – enabling agents to take real actions within business workflows.
• Apply MLOps best practices: model versioning and registry (MLflow), CI/CD for ML pipelines, drift detection, A/B testing, and performance monitoring in production.
• Collaborate with business stakeholders to frame problems, define success metrics, and translate requirements into scalable AI/data solutions.
• Ensure responsible AI: model explainability, fairness and bias auditing, data privacy compliance, and alignment with CNH governance standards.
• Conduct code and model reviews; contribute to shared libraries, best practices, and the CNH AI Center of Excellence.
• Maintain comprehensive technical documentation including data dictionaries, model cards, agent architecture diagrams, and operational runbooks.

Experience Required

• 5+ years of hands-on experience in data science, machine learning, or AI engineering in complex enterprise environments.
• Strong proficiency in Python: pandas, NumPy, scikit-learn, PyTorch or TensorFlow/Keras
• Proven experience building, validating, and deploying ML models to production (batch and real-time inference)
• Experience with cloud platforms (Azure preferred, or AWS / GCP) and managed ML services (Azure ML, SageMaker, Vertex AI)
• Hands-on experience with Large Language Models (LLMs) and prompt engineering (Anthropic Claude, OpenAI GPT, or similar)
• Practical experience building AI agents or agentic workflows using frameworks such as Copilot Studio, AI Foundry, Claude Agent SDK, LangChain, LangGraph, AutoGen, or equivalent – including tool use, memory management, and multi-step planning
• Knowledge of MLOps practices: experiment tracking (MLflow), model monitoring, CI/CD for ML, data and concept drift detection
• Experience with SQL and big data / cloud warehouse platforms (Databricks, Snowflake, Azure Synapse, or similar)
• Experience in at least one industry SDLC tool (Jira / Azure DevOps), source code management (Git), and CI/CD pipelines
• Strong understanding of statistical methods, data structures, and algorithmic thinking
• Ability to translate business problems into data science formulations and communicate results to non-technical audiences
• A quality and responsibility mindset:
• Write clean, modular, well-documented, and testable code
• Value data accuracy, model transparency, and reproducibility
• Communicate proactively and collaborate across functions
• The ability to coach and mentor others
• Strong verbal, written and interpersonal skills (team player)
• Professional proficiency in English (verbal and written)
• Experience with MCP (Model Context Protocol) server development for agent tool integration
• Knowledge of RAG (Retrieval-Augmented Generation), vector databases, and embedding pipelines
• Experience with multi-agent orchestration and human-in-the-loop frameworks
• Familiarity with responsible AI
• Manufacturing, agriculture, or industrial domain knowledge
• Experience with graph databases or knowledge graphs for AI reasoning

Preferred Qualifications

B.S. or M.S. in Computer Science, Data Science, Mathematics, Statistics, or a related field

What We Offer

At CNH, our people are at the heart of everything we do. That’s why we offer a comprehensive benefits program designed to support your health, well-being, and long-term success. From competitive compensation to flexible work arrangements and opportunities for continuous development, our benefits reflect our commitment to creating an environment where employees feel supported and empowered—both personally and professionally. We believe that when you’re given the tools to thrive, you can drive meaningful impact. At CNH, you’ll not only find the resources to succeed today—you’ll find the foundation to grow a career and build a future.