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Key Responsibilities:

• Lead the development and deployment of sophisticated AI, machine learning, and generative AI models, particularly leveraging Python and deep learning frameworks like PyTorch.
• Architect and optimize AI solutions using cloud platforms including Azure, AWS, and GCP, ensuring scalability, security, and performance.
• Drive innovation in natural language processing (NLP), natural language understanding (NLU), and multimodal modeling to enhance product capabilities and customer experiences.
• Design and execute large-scale proof-of-concept projects using generative AI frameworks such as LangChain, RAG, and VectorDBs, applying model quantization and optimization techniques for efficiency.
• Implement robust data pipelines and MLOps processes for smooth integration and production deployment of AI models, collaborating closely with software engineering teams.
• Conduct comprehensive data analysis, feature engineering, and model validation to ensure high-quality, reliable, and interpretable AI outcomes.
• Engage in continuous research to stay current with advancements in AI, deep learning, and healthcare analytics, and translate these insights into practical applications.
• Champion the ethical use of AI by collaborating with Responsible Use of AI (RUAI) teams to adhere to best practices, data privacy regulations, and compliance standards.
• Communicate technical findings and project progress effectively to diverse stakeholders, including senior leadership, clients, and interdisciplinary teams.

Preferred Qualifications:

• Extensive experience in AI and ML with a strong foundation in AI/ML best practices, ethics, and governance frameworks.
• Demonstrated ability to work effectively within distributed, multicultural teams and navigate the challenges of global collaboration.
• Proven expertise in generative AI technologies, large language models (LLMs), and applied research in transformer architectures such as GPT, Llama, and Mistral.
• Strong programming skills with Python, advanced SQL capabilities, and familiarity with collaborative code management using GitHub.
• Experience with GPU computing environments and rapid prototyping for experimental AI workflows.
• Deep understanding of traditional statistical machine learning and modern deep learning methodologies with applications to time series analysis, document processing, and image analytics.
• Exceptional analytical, problem-solving, and communication skills, capable of translating technical concepts for a broad audience.

Core Competencies:

• Client Centricity – anticipating and meeting customer needs with agile, tailored AI solutions.
• Passion for Results – driving projects to successful completion with high impact and measurable outcomes.
• Execution Excellence – delivering robust, quality-focused AI applications following rigorous standards.
• Collaborative Working – fostering teamwork across diverse global groups to co-create innovative solutions.
• Learning Agility – continuously updating skills and embracing emerging AI technologies.
• Problem Solving & Decision Making – effectively analyzing challenges and implementing strategic solutions.
• Effective Communication – clearly articulating complex ideas and findings to varied audiences.