Advanced AI Research Scientist Manager
Accenture - Carmel, IN
posted 2 days ago
About the position
Accenture is helping companies use generative AI to reinvent their enterprise and optimize business functions for breakthrough innovation and competitive advantage. With over 1,600 professionals dedicated to generative AI, leveraging the depth and experience of more than 40,000 AI and data professionals across the company, our Generative AI and LLM Center of Excellence brings together our Experienced Innovation, Strategic Investment, Exceptional Talent, and Power Ecosystem. As an Advanced Senior AI Research Scientist, you formulate real-world problems into practical, efficient, and scalable AI and Machine Learning problems. You lead teams and provide guidance to explore and implement new methodologies, model building techniques, and cutting-edge algorithms, applying these techniques with the right architecture to solve real-world problems. You have a deep understanding and ability to remain at the forefront of generative AI, LLM, and multi-modal models, focusing on driving innovation by applying these techniques to new business problems, use cases, and scenarios. As needed by the specific problem, you train and/or fine-tune generative AI models and evaluate them on the specific problem. A significant part of this role involves justifying the value of innovative generative AI or traditional Machine Learning approaches (or a combination of both) in business problems, and constructing methodologies that clearly demonstrate their value. You'll also work collaboratively with teams & leaders from both the business and technical side, including users, use case representatives, business owners, engineers, architects, and UI designers, to achieve end-to-end project development goals.
Responsibilities
- Participate in internal and external discussions to gather business use case requirements, provide on-the-spot AI expertise and AI solution options for business problems.
- Design, develop and implement advanced AI/ML models, especially LLM and other Gen AI models from scratch or existing foundation models via self-supervised learning, transferred-learning, and fine-tuning techniques.
- Design, develop and implement highly sophisticated Gen AI based applications including generative agent and similar architectures which support multiple Gen AI models to work together for complex tasks.
- Lead technical teams and grow true AI expertise within the broader team including offshore.
- Collaborate seamlessly with diverse, cross-functional teams to accurately identify and prioritize requirements, ensuring that the AI solutions meet the needs and expectations of various stakeholders.
- Develop and execute an AI solution project plan with team, timeline, and infrastructure dependency.
- Define and implement a value justification approach to the AI solutions; estimate solution cost with right technological choices; and calculate ROI.
- Create and maintain comprehensive technical documentation that captures the intricate details of the solution, captures IP, facilitating seamless understanding, knowledge transfer and future development.
- Collaborate with academia partners to stay on the cutting edge of AI, especially Gen AI technologies, providing thought leadership on AI trends, AI use case innovation trends, new AI opportunities, or foreseeable limitations, risks, and concerns.
Requirements
- Minimum of 6 years of experience in designing and developing neural network models, especially deep learning models, and Foundation models.
- Minimum of 6 years of experience in building, fine-tuning Foundation models including LLMs and multi-modal models.
- Minimum of 6 years of strong working knowledge of the different technologies, their differences, modalities in the Generative AI space.
- Minimum of 6 years of working knowledge and familiarity with different LLM driven application architecture patterns.
- Minimum of 6 years of experience in deep learning and neural networks, particularly training and large language models with popular libraries and GPUs.
- Minimum of 6 years of working knowledge of computer architecture, and familiarity with the fundamentals of GPU architecture.
- Minimum of 6 years of proven experience with processor and system-level performance modelling.
- Minimum of 3 years of experience in technical team management or team mentoring.
- Bachelor's degree or equivalent (minimum 12 years) work experience. (If Associate's Degree, must have minimum 6 years work experience)
