Career Area:

Job Description:

Job Summary:

Join the AI Research & Development team of Cat Digital and play a central role in advancing the frontier of applied AI for one of the world's largest industrial enterprises. As a Senior Data Scientist, you will design, build, and evaluate cutting-edge AI systems, spanning generative AI, large language models (LLMs), multimodal intelligence, retrieval-augmented generation (RAG), and autonomous agents, delivering high-impact Proofs of Concept (POCs) with clear production intent while exploring longer-horizon research opportunities.

What You Will Do:

• Design and execute AI experiments across the full model lifecycle: hypothesis formulation, data preparation, model development, evaluation, and iteration, maintaining research rigor in an ambiguous, fast-moving environment.

• Develop, fine-tune, and benchmark LLMs and multimodal AI models (text, vision, speech), including systematic evaluation of quality, latency, cost, and safety tradeoffs across model variants and providers.

• Explore and optimize knowledge retrieval systems (RAG pipelines, vector databases, hybrid search) and agentic workflows, ensuring relevance, accuracy, and scalability for enterprise use cases.

• Lead data preparation workstreams for model training, fine-tuning, and validation, including dataset curation, labeling strategy, synthetic data generation, and quality assurance.

• Instrument AI systems for observability and reproducibility using experiment tracking frameworks (e.g., Langfuse, MLflow), maintaining clear documentation of model versions, evaluation datasets, and performance baselines.

• Translate research findings into production-ready prototypes, collaborating with Engineering and Product teams to define technical requirements, integration paths, and deployment readiness criteria.

• Evaluate emerging AI capabilities and tools (open-source and commercial), providing structured assessments and recommendations to inform the team's technology strategy.

• Mentor and coach junior Data Scientists, establishing best practices for experimentation, model evaluation, and responsible AI development across the team.

• Communicate insights and results to technical and non-technical stakeholders, including product managers, engineers, and senior leadership, with clarity and business impact framing.

What You Will Have:

• Applied Statistics & Quantitative Methods: Experience applying statistical thinking to experimentation, evaluation, and decision‑making in ambiguous, research‑driven environments. 

• Analytical Rigor & Attention to Detail: Proven ability to design precise experiments, validate assumptions, and ensure accuracy and reproducibility of results. 

• Advanced Machine Learning & AI: Knowledge of modern ML techniques, including deep learning, generative AI, NLP, computer vision, and multimodal systems, with hands‑on implementation experience. 

• Model Evaluation & Optimization: Strong experience evaluating model quality and system‑level tradeoffs across accuracy, latency, cost, and scalability dimensions. 

• Programming Expertise: Proficiency in Python for AI and ML development, including use of modern AI frameworks and tooling. 

• Data Engineering & Access: Strong understanding of data storage, retrieval, and processing systems required to support large‑scale training and experimentation workflows. 

• Requirements & Systems Thinking: Ability to define technical and non‑functional requirements that bridge research, engineering, and production concerns.

Considerations for Top Candidates:

• Bachelor’s, Master’s, or PhD degree in Data Science, Computer Science, Machine Learning, Statistics, Applied Mathematics, Engineering, or a closely related technical field. 

• Proven experience building and deploying advanced ML models beyond traditional analytics use cases. 

• Extensive proficiency in Python (NumPy, Pandas, PyTorch, LangChain, etc.); ability to write clean, maintainable, production-oriented code and contribute to shared AI infrastructure.

• Strong hands‑on experience with generative AI, large language models, deep neural networks, and modern ML frameworks. 

• Demonstrated experience designing evaluation frameworks and benchmarks for AI systems. 

• Familiarity with AI infrastructure, cloud platforms (AWS, Azure), and scalable experimentation environments. 

• Advanced experience with version control, experiment tracking, and collaborative development (e.g., Git‑based workflows). 

• Experience working in Agile, cross‑functional product development environments. 

• Prior exposure to industrial, manufacturing, heavy equipment, or complex physical systems is a strong plus, but not required. 

Summary Pay Range:

Compensation and benefits offered may vary depending on multiple individualized factors, job level, market location, job-related knowledge, skills, individual performance and experience. Please note that salary is only one component of total compensation at Caterpillar. 

Benefits:

Subject to plan eligibility, terms, and guidelines. This is a summary list of benefits.

• Medical, dental, and vision benefits*

• Paid time off plan (Vacation, Holidays, Volunteer, etc.)*

• 401(k) savings plans*

• Health Savings Account (HSA)*

• Flexible Spending Accounts (FSAs)*

• Health Lifestyle Programs*

• Employee Assistance Program*

• Voluntary Benefits and Employee Discounts*

• Career Development*

• Incentive bonus*

• Disability benefits

• Life Insurance

• Parental leave

• Adoption benefits

• Tuition Reimbursement

* These benefits also apply to part-time employees

Posting Dates: