Lead Data Scientist – Artificial Intelligence R&D

Role Overview

• Stay current with emerging AI research by conducting ongoing literature reviews across core AI workstreams such as speech/voice, vision, multimodal systems, retrieval, and autonomous agents, and actively apply relevant innovations to Cat Digital’s AI R&D portfolio.
• Assess and compare academic and industry advancements to guide architecture choices, experimentation strategy, and production‑readiness decisions.
• Synthesize research findings into practical, enterprise‑relevant insights that influence prototyping priorities and long‑term AI strategy.
• Lead hands‑on experimentation and development of advanced machine learning and generative AI solutions, including LLMs, multimodal models (text, vision, speech), retrieval ‑ augmented generation (RAG), agents, and simulation/digital ‑ twin use cases.
• Design, build, and curate high ‑ quality datasets for training, fine ‑ tuning, validation, and evaluation of AI models at scale.
• Define and execute rigorous model evaluation strategies, including benchmarking model quality, accuracy, latency, cost, robustness, and safety tradeoffs.
• Drive rapid prototyping and POC development with a strong focus on reproducibility, experiment tracking, and observability to enable informed technical decision ‑ making.
• Research, compare, and optimize model architectures, algorithms, and AI system designs to improve performance, scalability, and enterprise readiness.
• Partner with Product and Engineering teams to translate research outcomes and prototypes into production ‑ ready capabilities, including defining technical requirements and success metrics.
• Communicate complex technical findings and insights clearly to both technical and non ‑ technical stakeholders, influencing roadmap and investment decisions.

Requirements

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

Tech Stack

• AWS
• Azure
• Cloud
• Numpy
• Pandas
• Python
• PyTorch

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