Line of Service
AdvisoryIndustry/Sector
Not ApplicableSpecialism
Product InnovationManagement Level
ManagerJob Description & Summary
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.To really stand out and make us fit for the future in a constantly changing world, each and every one of us at PwC needs to be a purpose-led and values-driven leader at every level. To help us achieve this we have the PwC Professional; our global leadership development framework. It gives us a single set of expectations across our lines, geographies and career paths, and provides transparency on the skills we need as individuals to be successful and progress in our careers, now and in the future.
As a Manager, you'll work as part of a team of problem solvers, helping to solve complex business issues from strategy to execution. PwC Professional skills and responsibilities for this management level include but are not limited to:
AI Engineer
Overview
We are seeking an exceptional AI Engineer to drive the development, optimization, and deployment of cutting-edge generative AI solutions for our clients. This role is at the forefront of applying generative models to solve real-world business challenges, requiring deep expertise in both the theoretical underpinnings and practical applications of generative AI.
Core Qualifications
Advanced degree (MS/PhD) in Computer Science, Machine Learning, or related field with a focus on generative models
3+ years of hands-on 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 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
Technical Skills
Required
Demonstrated experience with large language models (LLMs) such as GPT, BERT, T5, etc.
Practical understanding of generative AI frameworks (e.g., Hugging Face Transformers, OpenAI GPT, DALL-E)
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 SageMaker, Azure ML, Google Vertex AI)
Preferred
Proficiency in optimizing generative models for inference (quantization, pruning, distillation)
Experience with distributed training of large-scale AI models
Experience with model serving technologies (e.g., TorchServe, TensorFlow Serving, Triton Inference Server)
Key Responsibilities
Architect and implement end-to-end generative AI solutions, from data preparation to production deployment
Develop custom AI models and fine-tune pre-trained 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 few-shot learning in production systems
Implement robust evaluation frameworks for generative AI outputs
Collaborate with cross-functional teams to integrate generative AI capabilities into existing systems
Address challenges related to bias, fairness, and ethical considerations in generative AI applications
Project Delivery
Lead the technical aspects of generative AI projects from pilot to production
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
The ideal candidate will have a proven track record of successfully deploying AI models in production environments, a deep understanding of the latest advancements in generative AI, and the ability to apply this knowledge to solve complex business problems. They should be passionate about pushing the boundaries of what's possible with generative AI and excited about the opportunity to shape the future of AI-driven solutions for our clients.
Education (if blank, degree and/or field of study not specified)
Degrees/Field of Study required:Degrees/Field of Study preferred:Certifications (if blank, certifications not specified)
Required Skills
Optional Skills
Desired Languages (If blank, desired languages not specified)
Travel Requirements
Not SpecifiedAvailable for Work Visa Sponsorship?
NoGovernment Clearance Required?
NoJob Posting End Date
October 30, 2024