Job Description

Line of Service Advisory
Industry/Sector FS X-Sector
Specialism Operations
Management Level Senior Associate
& Summary At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth.
Those in intelligent automation at PwC will focus on conducting process mining, designing next generation small- and large-scale automation solutions, and implementing intelligent process automation, robotic process automation and digital workflow solutions to help clients achieve operational efficiencies and reduce costs.
Why PWC
At PwC, you will be part of a vibrant community of solvers that leads with trust and creates distinctive outcomes for our clients and communities. This purpose-led and values-driven work, powered by technology in an environment that drives innovation, will enable you to make a tangible impact in the real world. We reward your contributions, support your wellbeing, and offer inclusive benefits, flexibility programmes and mentorship that will help you thrive in work and life. Together, we grow, learn, care, collaborate, and create a future of infinite experiences for each other. Learn more .
At PwC, we believe in providing equal employment opportunities, without any discrimination on the grounds of gender, ethnic background, age, disability, marital status, sexual orientation, pregnancy, gender identity or expression, religion or other beliefs, perceived differences and status protected by law. We strive to create an environment where each one of our people can bring their true selves and contribute to their personal growth and the firm's growth. To enable this, we have zero tolerance for any discrimination and harassment based on the above considerations.
Responsibilities:
Take a leadership role in designing, developing, and deploying advanced ML and GenAI models (including LLMs, transformers, diffusion models, embeddings) for high-impact real-world applications.
Drive the fine-tuning and optimization of pre-trained foundation models utilizing advanced techniques such as LoRA, prompt engineering, RAG, and transfer learning.
Oversee the construction and integration of innovative retrieval-augmented generation (RAG) pipelines with sophisticated vector databases like Pinecone, Weaviate, PostgreSQL + pgvector, FAISS.
Lead the implementation of scalable MLOps practices for data preprocessing, feature engineering, and model training pipelines.
Strategically collaborate with cloud AI platforms (AWS Bedrock, Azure OpenAI, GCP Vertex AI) for deployment, scaling, and maintenance of complex models.
Act as a liaison between product and engineering teams, embedding and guiding AI capabilities' strategic application into various software solutions.
Stay abreast of cutting-edge research and evolving trends in GenAI, NLP, multimodal AI, and applied ML, bringing innovative solutions and insights to the team.
Core Technical Skills (Must-Have):
Proficiency in programming with a strong grasp of Python and frameworks such as PyTorch, TensorFlow, and Hugging Face Transformers.
Extensive hands-on experience with LLMs, embeddings, text generation, summarization, semantic search, and fine-tuning.
In-depth understanding and proven experience with SQL/NoSQL databases, data pipelines, feature stores, and ETL processes for ML workloads.
Skilled with vector databases (FAISS, Pinecone, Weaviate, ChromaDB, and pgvector) and their strategic deployment in complex projects.
Advanced knowledge of MLOps tools: MLflow, Docker, CI/CD for ML models, model monitoring, ensuring robust lifecycle management.
Expertise in Cloud platforms: AWS (SageMaker, Bedrock), GCP (Vertex AI), or Azure (OpenAI), leveraging them for efficient and scalable AIML solutions.
Competency in APIs & Integration: REST, gRPC, FastAPI, Flask, with capability to wrap and serve models as sophisticated APIs.
Good to Have:
Knowledge of multimodal AI encompassing text, image, and speech processing.
Familiarity with RLHF (Reinforcement Learning with Human Feedback).
Experience with Kubernetes, Ray, or distributed training frameworks, optimizing them for advanced AIML solutions.
Mandatory skill sets:
Python, Keras, RAG, MLOPs, Azure/AWS, vector DB, SLM & LLM finetuning
Preferred skill sets:
Python, Keras, RAG, MLOPs, Azure/AWS, vector DB, SLM & LLM finetuning
Years of experience required:
4 to 7yrs
Education qualification:
Bachelor's degree in Engineering (B.E. Hons) or related field. Masters degree
Education (if blank, degree and/or field of study not specified) Degrees/Field of Study required: Bachelor of Engineering, Master Degree
Degrees/Field of Study preferred:
Certifications (if blank, certifications not specified)
Required Skills Artificial Intelligence Markup Language
Optional Skills Accepting Feedback, Accepting Feedback, Active Listening, Agile Methodology, Analytical Thinking, Automation Algorithms, Automation Engineering, Automation Framework Design and Development, Automation Programming, Automation Solutions, Automation Studio, Automation System Efficiency, Blue Prism, Business Analysis, Business Performance Management, Business Process Analysis, Business Process Automation (BPA), Business Transformation, Business Value Optimization, C++ Programming Language, Cognitive Automation, Communication, Conducting Discovery, Configuration Management (CM), Continuous Process Improvement {+ 36 more}
Desired Languages (If blank, desired languages not specified)
Travel Requirements Not Specified
Available for Work Visa Sponsorship? No
Government Clearance Required? No
Job Posting End Date

Skills Required