Manager Generative AI

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What We'll Bring:
Job Summary
As a Manager for Generative AI team, you will play a pivotal role in defining architecture, designing, developing, evaluating and deploying advanced generative AI models. You will be responsible for leveraging different architectures and RAG models to create sophisticated AI-driven solutions. This role requires a deep understanding of generative models, machine learning algorithms, and the ability to deliver on complex AI projects.
Years of Experience: 14+ Years
Key Responsibilities• Design, develop, and optimize generative AI models with a strong focus on RAG and Graph RAG.• Implement state-of-the-art techniques for retrieval-augmented generation and graph-based AI models.• Apply RAG models to enhance information retrieval and generation tasks, improving the quality and accuracy of AI outputs.• Develop custom AI models and fine-tune pre-trained models for specific client use cases• Optimize generative models for production, balancing performance, latency• Design and implement efficient data pipelines for training and serving generative models• Develop strategies for effective prompt engineering and few-shot learning in production systems• Implement robust evaluation frameworks for generative AI outputs• Address challenges related to bias, fairness, and ethical considerations in generative AI applications• Develop internal tools and frameworks to accelerate generative AI development• Mentor and guide junior developers in generative AI techniques and best practices.• Stay updated with the latest research in generative AI, RAG, and Graph RAG, and apply new methodologies to improve model outcomes.• Experiment with different model architectures and approaches to achieve optimal results.
What You'll Bring:
Project Delivery

• Lead the technical aspects of generative AI projects from pilot to production
• Deploy AI models into production environments, ensuring scalability, efficiency, and reliability.
• Collaborate with DevOps teams to seamlessly integrate models into existing systems and workflows.
• Develop proof-of-concepts 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

Client Engagement

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

Innovation and Knowledge Sharing

• Stay at the forefront of generative AI research and industry trends
• Contribute to the company's 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

Impact You'll Make:
Technical Skills

• Required
  • Strong programming skills in languages such as Python, Java, or C++
  • Solid understanding of machine learning algorithms and techniques
  • Demonstrated experience with latest large language models (LLMs)
  • Practical understanding of generative AI frameworks (e.g., Hugging Face Transformers, OpenAI GPT, LlamaIndex, Jarvis etc)
  • Extensive experience with RAG (Retrieval-Augmented Generation) and GraphRAG models.
  • Familiarity with prompt engineering and few-shot learning techniques
  • Expertise in MLOps and LLMOps practices, including CI/CD for ML models
  • Strong knowledge of one or more cloud-based AI services (e.g., AWS Bedrock, Azure ML, Google Vertex AI)
  • Deep understanding of state-of-the-art AI architectures (e.g., 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

• Preferred
  • Proficiency in optimizing generative models for inference (quantization, pruning, distillation)
  • Experience with distributed training of large-scale AI models
  • Advanced Techniques: Experience with reinforcement learning, unsupervised learning, or graph-based learning models.
  • Agile Methodologies: Experience working in Agile/Scrum environments.
  • Version Control: Proficiency with Git and other version control systems.

Qualifications

• Advanced degree in Computer Science, Machine Learning, or related field with a focus on generative models
• 12+ years of hands-on experience developing and deploying AI models in production environments with 2+ years of experience in developing generative AI pilots, proofs of concept, and prototypes

This is a hybrid position and involves regular performance of job responsibilities virtually as well as in-person at an assigned TU office location for a minimum of two days a week.
TransUnion Job Title
Manager I, Applications Development