Industry/Sector

Specialism

Management Level

Job Description & Summary

Focused on relationships you are building meaningful client connections and learning how to manage and inspire others. Navigating increasingly complex situations you are growing your personal brand deepening technical expertise and awareness of your strengths. You are expected to anticipate the needs of your teams and clients and to deliver quality. Embracing increased ambiguity you are comfortable when the path forward isnt clear you ask questions and you use these moments as opportunities to grow.

Examples of the skills knowledge and experiences you need to lead and deliver value at this level include but are not limited to:

• Respond effectively to the diverse perspectives needs and feelings of others.
• Use a broad range of tools methodologies and techniques to generate new ideas and solve problems.
• Use critical thinking to break down complex concepts.
• Understand the broader objectives of your project or role and how your work fits into the overall strategy.
• Develop a deeper understanding of the business context and how it is changing.
• Use reflection to develop self awareness enhance strengths and address development areas.
• Interpret data to inform insights and recommendations.
• Uphold and reinforce professional and technical standards (e.g. refer to specific PwC tax and audit guidance) the Firms code of conduct and independence requirements.

Key Responsibilities

• Collaborate across teams: Partner with cross-functional groups to understand business requirements and identify opportunities for GenAI technology.
• Develop algorithms: Design and build advanced deep learning algorithms for generative models.
• Integrate AI solutions: Incorporate generative AI into existing workflow systems for smooth adoption.
• Research advancements: Stay up-to-date with the latest generative AI technologies and methodologies.
• Optimize performance: Fine-tune and enhance generative models for peak performance and efficiency.
• Troubleshoot implementations: Diagnose and resolve issues related to generative AI models and deployments.
• Documentation: Create and maintain comprehensive documentation detailing generative AI models and their applications.
• Communicate findings: Translate complex technical concepts for non-technical stakeholders.

Required Qualifications

• Experience: 3 years in data science or applied ML with shipped solutions; strong Python proficiency.
• Practical LLM experience: Building RAG pipelines prompt/chain design and experience with supervised or adapter-based tuning (LoRA/QLoRA).
• NLP/ML Tooling: Proficiency with PyTorch or TensorFlow scikit-learn and the Hugging Face ecosystem.
• Web development: Familiarity with Python web frameworks (Flask FastAPI) for AI model web applications.
• Cloud-native development: REST APIs microservices serverless functions.
• Retrieval & vector search: Experience with embeddings vector databases and ranking/re-ranking techniques.
• Evaluation & experimentation: Designing metrics A/B testing with sound statistical methods.
• Data skills: Strong SQL abilities; working with data lakes/warehouses and orchestration tools.
• MLOps/LLMOps: Experiment tracking (MLflow/Weights & Biases) model packaging CI/CD for ML monitoring and incident response.
• Cloud deployment: Experience with Azure and/or AWS; containerization with Docker and Kubernetes.
• Communication: Ability to translate business needs into technical plans and communicate results clearly to diverse audiences.

Preferred Skills

• Frameworks: LangChain Semantic Kernel LlamaIndex; Azure OpenAI/OpenAI/Anthropic; Guardrails/safety toolkits (e.g. Azure AI Content Safety Presidio).
• Fine-tuning & data generation: Dataset curation synthetic data creation RLHF/RLAIF exposure.
• Agents & tool-use: Function calling planning orchestration of multi-step agents.
• Performance engineering: Model distillation quantization ONNX/Triton Ray for scaling.
• Event-driven integration: Kafka/Event Hubs streaming inference with backpressure and retries.
• Certifications: Azure AI Engineer/Data Scientist Databricks or AWS ML Specialty.

Professional & Educational Background

• Bachelor Degree in Computer Science Data Science Statistics Engineering or equivalent

Travel Requirements

Job Posting End Date