IN_Manager_AI/ML Engineer_GCC_Advisory_Hyderabad

Line of Service
Advisory
Industry/Sector
Not Applicable
Specialism
Data, Analytics & AI
Management Level
Manager
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.
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 about us.
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.
Job Description & Summary:
We're looking for a Senior AI/ML Engineer who can design, build, and deploy scalable ML, GenAI, and Agentic AI systems across cloud environments with strong focus on productionization, automation, and business impact. You'll work across demand forecasting, RAG-based intelligent applications, autonomous multi-agent systems, and enterprise AI integration.
Responsibilities:
Build end-to-end ML/AI pipelines (data → model → deployment → monitoring)
Develop and deploy ML, Deep Learning, NLP, and GenAI models in production
Design and implement RAG systems — retrieval, chunking, embeddings, vector search, and prompt engineering
Build Agentic AI solutions — autonomous agents, multi-agent workflows, tool-calling, planning, and memory
Build and optimize time series forecasting models (demand forecasting, inventory planning)
Implement MLOps pipelines — CI/CD, model monitoring, drift detection, governance
Optimize models for performance, cost, and latency
Integrate AI systems with enterprise APIs, data platforms, and customer-facing applications
Design scalable LLM inference architectures for efficient deployment
Collaborate with data scientists, product managers, engineers, and business stakeholders in Agile teams
Debug, optimize, and enhance ML models for quality and performance improvements
Mentor team members and present technical findings to diverse audiences
Stay current with AI/GenAI trends and evaluate emerging tools and frameworks
Mandatory skill sets:
Build end-to-end ML/AI pipelines (data → model → deployment → monitoring)
Develop and deploy ML, Deep Learning, NLP, and GenAI models in production
Design and implement RAG systems — retrieval, chunking, embeddings, vector search, and prompt engineering
Build Agentic AI solutions — autonomous agents, multi-agent workflows, tool-calling, planning, and memory
Build and optimize time series forecasting models (demand forecasting, inventory planning)
Implement MLOps pipelines — CI/CD, model monitoring, drift detection, governance
Optimize models for performance, cost, and latency
Integrate AI systems with enterprise APIs, data platforms, and customer-facing applications
Design scalable LLM inference architectures for efficient deployment
Collaborate with data scientists, product managers, engineers, and business stakeholders in Agile teams
Debug, optimize, and enhance ML models for quality and performance improvements
Mentor team members and present technical findings to diverse audiences
Stay current with AI/GenAI trends and evaluate emerging tools and frameworks
Preferred skill sets:
Build end-to-end ML/AI pipelines (data → model → deployment → monitoring)
Develop and deploy ML, Deep Learning, NLP, and GenAI models in production
Design and implement RAG systems — retrieval, chunking, embeddings, vector search, and prompt engineering
Build Agentic AI solutions — autonomous agents, multi-agent workflows, tool-calling, planning, and memory
Build and optimize time series forecasting models (demand forecasting, inventory planning)
Implement MLOps pipelines — CI/CD, model monitoring, drift detection, governance
Optimize models for performance, cost, and latency
Integrate AI systems with enterprise APIs, data platforms, and customer-facing applications
Design scalable LLM inference architectures for efficient deployment
Collaborate with data scientists, product managers, engineers, and business stakeholders in Agile teams
Debug, optimize, and enhance ML models for quality and performance improvements
Mentor team members and present technical findings to diverse audiences
Stay current with AI/GenAI trends and evaluate emerging tools and frameworks
Years of experience required:
7-12 years
Education qualification:
Bachelor’s or Master’s degree in Computer Science, Engineering, or related field (60% above)
Education (if blank, degree and/or field of study not specified)
Degrees/Field of Study required: Bachelor of Technology, Bachelor of Engineering
Degrees/Field of Study preferred:
Certifications (if blank, certifications not specified)
Required Skills
Snowflake (Platform)
Optional Skills
Accepting Feedback, Accepting Feedback, Active Listening, AI Fluency, AI-Human Collaboration, Algorithm Development, Alteryx (Automation Platform), Analytical Thinking, Analytic Research, Big Data, Business Data Analytics, Coaching and Feedback, Communication, Complex Data Analysis, Conducting Research, Creativity,