Machine Learning Engineer - Senior Associate

Industry/Sector

Not Applicable

Specialism

Data, Analytics & AI

Management Level

Senior Associate

Job Description & Summary

At PwC, our people in data and analytics focus on leveraging data to drive insights and make informed business decisions. They utilise advanced analytics techniques to help clients optimise their operations and achieve their strategic goals.

In data analysis at PwC, you will focus on utilising advanced analytical techniques to extract insights from large datasets and drive data-driven decision-making. You will leverage skills in data manipulation, visualisation, and statistical modelling to support clients in solving complex business problems.

PwC US - Acceleration Center is looking for an experienced and visionary GenAI Data Engineer to join our team as a Manager. This leadership role involves overseeing the development and maintenance of data pipelines, the implementation of machine learning models, and the optimization of data infrastructure for our GenAI projects. The ideal candidate will have an extensive background in data engineering, with a deep focus on GenAI technologies, and a solid understanding of data processing, event-driven architectures, containerization, and cloud computing.

 

Years of Experience: 5+ years in data science or machine-learning-driven product development, 1-2 years of which include leading GenAI or LLM initiatives and managing people or project teams. 

 

Responsibilities: 

 

Leadership & Strategy:

• Own the GenAI product roadmap – prioritize use cases, set measurable OKRs, and align delivery with business strategy.
• Lead, coach, and grow a multi-disciplinary team (data scientists, MLOps engineers, full-stack developers).
• Champion Responsible AI – establish governance, bias-mitigation, model-monitoring, and privacy-by-design practices.
• Stakeholder engagement – translate complex AI concepts into executive-ready narratives; influence partners and clients. 

 

Technical Excellence:

• Design, architect, and iterate GenAI and agentic AI solutions end-to-end (LLM orchestration, RAG pipelines, goal-directed agents).
• Build scalable data pipelines for structured & unstructured data: intelligent chunking, embeddings, vector stores (FAISS, pgvectors, Azure AI Search).
• Oversee robust MLOps – containerize workloads, implement CI/CD, deploy to Kubernetes across Azure, AWS, or GCP.
• Promote engineering best practices – clean architecture, unit/integration tests, GitFlow, code reviews, automated documentation. 

 

Requirements:

• 2-4 years of relevant experience in data science, with significant expertise in GenAI projects.
• Experience integrating GenAI with Azure OpenAI, AWS Bedrock, GCP Vertex AI, or similar managed services.
• Advanced programming skills in Python and proficiency in machine learning libraries like TensorFlow, PyTorch, or scikit-learn.
• Working experience in code migration use cases using Gen AI (especially for stored processes, macros, batch jobs, etc.).
• Has proficiency in SAS
• Has worked in R, Scala, Matlab or SQL
• Agentic AI experience with LLM-backed agent frameworks including LangChain, LangGraph, AutoGen, and CrewAI, as well as RAG patterns.
• Extensive experience in data preprocessing, feature engineering, and statistical analysis.
• Strong knowledge of cloud computing platforms such as AWS, Azure, or Google Cloud, and data visualization techniques.
• Demonstrated leadership in managing data science teams and projects.
• Exceptional problem-solving, analytical, and project management skills.
• Excellent communication and interpersonal skills, with the ability to lead and collaborate effectively in a dynamic environment. 

 

Preferred Qualifications:

• Bachelor's or Master's in Computer Science, Data Science, Statistics, or related discipline.
• Certifications in cloud (Azure/AWS/GCP), Kubernetes, or GenAI technologies.
• Having finance background, or experience working with Finance or Banking domain 

 

Nice to Have Skills:

• Experience implementing Model Context Protocol (MCP) and sophisticated agent-to-agent (A2A) communication.
• Advanced model performance – lead experiments on fine-tuning, quantization (LoRA, QLoRA, PEFT) and evaluation (BLEU, ROUGE, toxicity, factuality).
• Object-oriented programming with Java, C++, or C#.
• Hands-on experience with leading agent orchestration platforms such as Agentspace (Google), Agentforce (Salesforce), and Mosaic AI (Databricks).
• Experience in Spark/Hadoop is preferred 

 

Educational Background:

• BE / B.Tech / MCA / M.Sc / M.E / M.Tech /Master’s Degree /MBA / Any degree 

Travel Requirements

Not Specified

Job Posting End Date