Gen AI Manager

A career within our Infrastructure practice will provide you with the opportunity to design, build, coordinate and maintain the IT environments for clients to run internal operations, collect data, monitor, develop and launch products.

Infrastructure management consists of hardware, storage, compute, network and software layers.

As a part of our Infrastructure Engineering team, you will be responsible for maintaining the critical IT systems which includes build, run and maintenance while providing technical support and training that aligns to industry leading practices.

• Develop new skills outside of comfort zone.
  
  
• Act to resolve issues which prevent the team working effectively.
  
  
• Coach others, recognise their strengths, and encourage them to take ownership of their personal development.
  
  
• Analyse complex ideas or proposals and build a range of meaningful recommendations.
  
  
• Use multiple sources of information including broader stakeholder views to develop solutions and recommendations.
  
  
• Address substandard work or work that does not meet firms/clients expectations.
  
  
• Use data and insights to inform conclusions and support decisionmaking.
  
  
• Develop a point of view on key global trends, and how they impact clients.
  
  
• Manage a variety of viewpoints to build consensus and create positive outcomes for all parties.
  
  
• Simplify complex messages, highlighting and summarising key points.
  
  
• Uphold the firms code of ethics and business conduct.
  
  

• Advanced degree (MS/PhD) in Computer Science, Machine Learning, or related field with a focus on generative models
• 3+ years of handson experience developing and deploying AI models in production environments with 1 year of experience in developing generative AI pilots, proofs of concept, and prototypes
• Deep understanding of stateoftheart AI architectures (eg, Transformers, VAEs, GANs, Diffusion Models)
• Expertise in PyTorch or TensorFlow, with a preference for experience in both
• Proficiency in Python and software engineering best practices for AI systems

• Required
  • Demonstrated experience with large language models (LLMs) such as GPT, BERT, T5, etc
  • Practical understanding of generative AI frameworks (eg, Hugging Face Transformers, OpenAI GPT, DALLE)
  • Familiarity with prompt engineering and fewshot learning techniques
  • Expertise in MLOps and LLMOps practices, including CI/CD for ML models
  • Strong knowledge of one or more cloudbased AI services (eg, AWS SageMaker, Azure ML, Google Vertex AI)
• Preferred
  • Proficiency in optimizing generative models for inference (quantization, pruning, distillation)
  • Experience with distributed training of largescale AI models
  • Experience with model serving technologies (eg, TorchServe, TensorFlow Serving, Triton Inference Server)

• Architect and implement endtoend generative AI solutions, from data preparation to production deployment
• Develop custom AI models and finetune pretrained models for specific client use cases
• Optimize generative models for production, balancing performance, latency, and resource utilization
• Design and implement efficient data pipelines for training and serving generative models
• Develop strategies for effective prompt engineering and fewshot learning in production systems
• Implement robust evaluation frameworks for generative AI outputs
• Collaborate with crossfunctional teams to integrate generative AI capabilities into existing systems
• Address challenges related to bias, fairness, and ethical considerations in generative AI applications

• Lead the technical aspects of generative AI projects from pilot to production
• Develop proofofconcepts and prototypes to demonstrate the potential of generative AI in solving client problems
• Conduct technical feasibility studies for applying generative AI to novel use cases
• Implement monitoring and observability solutions for deployed generative models
• Troubleshoot and optimize generative AI systems in production environments

• Provide expert technical guidance on generative AI capabilities and limitations to clients
• Collaborate with solution architects to design generative AIpowered solutions that meet client needs
• Present technical approaches and results to both technical and nontechnical stakeholders
• Assist in scoping and estimating generative AI projects

• Stay at the forefront of generative AI research and industry trends
• Contribute to the companys intellectual property through patents or research publications
• Develop internal tools and frameworks to accelerate generative AI development
• Mentor junior team members on generative AI technologies and best practices
• Contribute to technical blog posts and whitepapers on generative AI applications

Degrees/Field of Study required Degrees/Field of Study preferred Acceptance Test Driven Development (ATDD), Acceptance Test Driven Development (ATDD), Accepting Feedback, Active Listening, Analytical Thinking, API Management, Application Development, Application Frameworks, Application Lifecycle Management, Application Software, Business Process Improvement, Business Process Management (BPM), Business Requirements Analysis, C++ Programming Language, Client Management, Coaching and Feedback, Code Review, Coding Standards, Communication, Computer Engineering, Computer Science, Continuous Integration/Continuous Delivery (CI/CD), Creativity, Debugging, Embracing Change {+ 35 more} No No