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.

 

Job Responsibilities

Combine vast data assets with advanced AI, including LLMs and Multimodal LLMsBridge scientific research and software engineering, applying expertise in both domainsCollaborate with engineering teams to lead the design and delivery of GenAI productsArchitect and implement scalable AI Agents, Agentic Workflows, and GenAI applicationsIntegrate GenAI solutions with enterprise platforms using API-based methodsEstablish validation procedures with Evaluation Frameworks, bias mitigation, safety protocols, and guardrailsAlign ML problem definition with business objectivesCommunicate technical information and ideas effectively to stakeholders

 

Required Qualifications, Capabilities, and Skills

PhD in a quantitative discipline such as Computer Science, Mathematics, or StatisticsTen years of experience in an individual contributor role in ML engineeringStrong understanding of statistics, optimization, and ML theory, focusing on NLP and/or Computer Vision algorithmsDemonstrated experience in parameter-efficient fine-tuning, model quantization, and quantization-aware fine-tuning of LLM modelsExperience integrating GenAI solutions with enterprise platforms via standardized API patternsAbility to establish validation procedures, including Evaluation Frameworks, bias mitigation, safety protocols, and guardrailsExcellent grasp of computer science fundamentals and SDLC best practicesStrong communication skills to build trust with stakeholders

 

Preferred Qualifications, Capabilities, and Skills

Experience designing and implementing pipelines using DAGs such as Kubeflow, DVC, or RayAbility to construct batch and streaming microservices exposed as gRPC or GraphQL endpointsHands-on experience implementing distributed, multi-threaded, and scalable applications using frameworks such as Ray, Horovod, or DeepSpeed

 

*** Relocation assistance is not available for this role.