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Accenture

Advanced AI Research Scientist Associate Manager

Accenture, San Diego, California, United States, 92189


We Are

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.

You Are

As an Advanced AI Research Scientist, you formulate real-world problems into practical, efficient, and scalable AI and Machine Learning problems.

You lead a team 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.

As a significant part of this role, you will be justifying the value of innovative generative AI or traditional Machine Learning approaches (or a combination of both) in the business problems, and you'll be expected to construct methodologies that clearly demonstrate their value.

You'll also work collaboratively with teams 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.

The Work

Participate in internal and external discussions to gather business use case requirements, providing on-the-spot AI expertise and AI solution options for business problems.

Design, develop, and implement advanced AI/ML models, especially LLMs 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 agents and similar architectures that 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 the right technological choices; and calculate ROI.

Create and maintain comprehensive technical documentation that captures the intricate details of the solution, capturing IP, facilitating seamless understanding, knowledge transfer, and future development.

Collaborate with academic 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.

Travel may be required for this role. The amount of travel will vary from 0 to 100% depending on business needs and client requirements.

Here's What You Need

Minimum of 4 years of experience in designing and developing neural network models, especially deep learning models and Foundation models.

Minimum of 4 years of experience in building and fine-tuning Foundation models including LLMs and multi-modal models.

Minimum of 4 years of strong working knowledge of different technologies and their differences in the Generative AI space.

Minimum of 4 years of working knowledge and familiarity with different LLM-driven application architecture patterns.

Minimum of 4 years of experience in deep learning and neural networks, particularly training large language models with popular libraries and GPUs.

Minimum of 4 years of working knowledge of computer architecture and familiarity with the fundamentals of GPU architecture.

Minimum of 4 years of proven experience with processor and system-level performance modeling.

Minimum of 2 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 a minimum of 6 years' work experience)

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