Senior Data Scientist – Artificial Intelligence R&D

Role Overview

• 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.

Requirements

• 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.

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