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Manager_ Expert AI

Manager_ Expert AI

PwC Service Delivery Center

8 - 13 years

14 - 17 Lacs

Gurugram

Posted:18 hours ago| Platform:

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Skills Required

Computer science Data modeling Coding Database administration Agile Workflow DBMS Apache Open source Python

Work Mode

Work from Office

Job Type

Full Time

Job Description

GPS XSector

Specialism

Operations

& 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 decisionmaking and driving business growth.
In data engineering at PwC, you will focus on designing and building data infrastructure and systems to enable efficient data processing and analysis. You will be responsible for developing and implementing data pipelines, data integration, and data transformation solutions.

& Summary At PwC, our purpose is to build trust in society and solve important problems. We re a network of firms in 157 countries with more than 300,000 people who are committed to delivering quality in Assurance, Advisory and Tax services. Within Advisory, PwC has a large team that focus on transformation in Government through Digital inclusion. The open position is for a candidate who desires to work with government clients and bring about a change in society. A successful candidate will be expected to work proactively and effectively on multiple client engagements over the period of time and take ownership of the entire project delivery he/she entrusted with.

1. Lead the design, development and deployment of advanced AI/ML models, particularly in the domains of NLP and Generative AI

2. Architect and implement endtoend solutions leveraging large language models (LLMs), transformers and deep learning architectures

3. Develop customized NLP pipelines for tasks such as text classification, summarization, entity recognition, semantic search and conversational AI

4. Drive innovation in generative AI use cases such as prompt engineering, text generation, RAG, multimodal AI and finetuning LLMs

5. Collaborate with product managers, data engineers and domain experts to translate business requirements into intelligent solutions

6. Mentor AI/ML teams and provide technical leadership on best practices, frameworks and emerging technologies

7. Ensure responsible AI practices including bias mitigation, model explainability and governance

8. Publish technical papers, contribute to opensource projects and represent the organization in AI forums and communities

9. Evaluate and integrate new AI tools, APIs and models into productiongrade systems

Mandatory skill sets

8+ years of experience in AI/ML, with deep expertise in NLP, Generative AI and applied Data Science Handson experience with LLMs (e.g., GPT, BERT, LLaMA, T5), transformer architectures and prompt engineering Strong coding and modeling experience using Python and ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face Transformers) Experience with NLP tasks like question answering, summarization, text generation, sentiment analysis, topic modeling Proven ability to finetune and deploy LLMs on domainspecific tasks and datasets Familiarity with vector databases (e.g., FAISS, Pinecone), embeddings and retrievalaugmented generation (RAG)

Strong foundation in statistics, probability and machine learning algorithms Proficiency with ML lifecycle tools (e.g., MLflow, DVC), containerization (Docker) and model deployment on cloud platforms (AWS, GCP, Azure) Excellent communication and leadership skills to influence stakeholders and guide teams

Preferred skill sets

Experience with reinforcement learning (RLHF), diffusion models or multimodal learning Knowledge of MLOps tools and workflow orchestration (e.g., Airflow, Kubeflow) Familiarity with ethical AI practices, model interpretability (e.g., SHAP, LIME) and AI compliance frameworks Experience with speechtotext, OCR or crosslingual NLP Contributions to research papers, patents or opensource AI/ML libraries Certification in AI/ML from recognized platforms or institutions (e.g., Stanford, Coursera, AWS, GCP)

Years of experience required

8+ years

Education qualification
Master s or bachelors degree in computer science, Artificial Intelligence, Data Science, Mathematics, Statistics or a related technical field. A Ph.D. is a plus.

Education

Degrees/Field of Study required Master Degree, Bachelor Degree

Degrees/Field of Study preferred

Required Skills

AI Programming, Standard ML (Programming Language)

Accepting Feedback, Accepting Feedback, Active Listening, Agile Scalability, Amazon Web Services (AWS), Analytical Thinking, Apache Airflow, Apache Hadoop, Azure Data Factory, Coaching and Feedback, Communication, Creativity, Data Anonymization, Data Architecture, Database Administration, Database Management System (DBMS), Database Optimization, Database Security Best Practices, Databricks Unified Data Analytics Platform, Data Engineering, Data Engineering Platforms, Data Infrastructure, Data Integration, Data Lake, Data Modeling {+ 32 more}

Travel Requirements

Government Clearance Required?

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