Applied AI Lead Data Scientist - Vice President

Overview

Join us as we revolutionize data and analytics with cutting‑edge Generative AI, shaping the future of our organization. Experience career growth, collaborate with top talent, and make a meaningful impact through ethical and sustainable AI practices.

As a Generative AI Data Science Lead in the Applied Solutions Team, you will drive the development and optimization of LLM‑aided AI products. You work closely with cross‑functional teams to deliver scalable solutions that support our business objectives and foster innovation. You will help shape the future of our organization by leveraging advanced data science and engineering practices. You will collaborate with the ML Centre of Excellence, AI Research, and Engineering teams to design and deliver high‑impact GenAI products and APIs.

Your expertise will ensure our solutions are robust, scalable, and aligned with the needs of our business and stakeholders.

• Combine vast data assets with advanced AI, including LLMs and Multimodal LLMs
• Bridge scientific research and software engineering, applying expertise in both domains
• Collaborate with engineering teams to lead the design and delivery of GenAI products
• Architect and implement scalable AI Agents, Agentic Workflows, and GenAI applications
• Integrate GenAI solutions with enterprise platforms using API‑based methods
• Establish validation procedures with Evaluation Frameworks, bias mitigation, safety protocols, and guardrails
• Align ML problem definition with business objectives
• Communicate technical information and ideas effectively to stakeholders

• Bachelor's Degree in a quantitative discipline such as Computer Science, Mathematics, or Statistics
• Ten years of experience in an individual contributor role in ML engineering
• Strong understanding of statistics, optimization, and ML theory, focusing on NLP and/or Computer Vision algorithms
• Demonstrated experience in parameter‑efficient fine‑tuning, model quantization, and quantization‑aware fine‑tuning of LLM models
• Experience integrating GenAI solutions with enterprise platforms via standardized API patterns
• Ability to establish validation procedures, including Evaluation Frameworks, bias mitigation, safety protocols, and guardrails
• Excellent grasp of computer science fundamentals and SDLC best practices
• Strong communication skills to build trust with stakeholders

• PhD in a quantitative discipline such as Computer Science, Mathematics, or Statistics
• Experience designing and implementing pipelines using DAGs such as Kubeflow, DVC, or Ray
• Ability to construct batch and streaming microservices exposed as gRPC or Graph
  
  QL endpoints
• Hands‑on experience implementing distributed, multi‑threaded, and scalable applications using frameworks such as Ray, Horovod, or Deep Speed

Relocation assistance is not available for this role.