IN_Senior Associate_ ML Engineer_GCC_Advisory_Bangalore

Advisory

Not Applicable

Data, Analytics & AI

Senior Associate

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. "

Responsibilities: •Design & Develop ML Models: Build, train, evaluate, and optimize machine learning models to solve complex business problems. 

• End-to-End ML Pipelines: Design and implement scalable, production-grade ML pipelines—from data ingestion, feature engineering, and model training to deployment, monitoring, and retraining. 

• Production Deployment: Deploy ML models at scale using AWS services, ensuring low-latency, high-availability, and fault-tolerant systems. 

• Data Engineering: Work with large-scale structured and unstructured datasets; build ETL pipelines to prepare data for model training and inference. 

• Research & Innovation: Stay current with the latest ML/AI research, evaluate new techniques, and drive adoption of cutting-edge methodologies. 

• Operational Excellence: Own the end-to-end lifecycle of ML models including monitoring, alerting, debugging, and continuous improvement. 

• Documentation & Communication: Write clear technical documentation and effectively communicate results and trade-offs to both technical and non-technical stakeholders. 

Mandatory skill sets: • Dynamics, AI, Selenium

Preferred skill sets: • 

• Programming: Strong proficiency in Python; experience with ML frameworks such as PyTorch, TensorFlow, or JAX. 

• ML Fundamentals: Solid understanding of supervised/unsupervised learning, deep learning, NLP, recommendation systems, and optimization techniques. Familiarity with MLOps practices—including CI/CD for ML, model versioning, feature stores, and automated retraining pipelines. 

• Data Skills: Experience with SQL and large-scale data platforms (e.g., Spark, Hadoop, Redshift, or equivalent). 

• Cloud & Infrastructure: Hands-on experience with AWS. 

• Software Engineering: Strong software development fundamentals, including data structures, algorithms, and system design. 

• Communication: Excellent written and verbal communication skills, with the ability to present complex technical concepts to senior leadership. 

 

Years of experience required: Experience: 5+ years of professional experience in machine learning engineering or applied ML. 

Education qualification: Education: Bachelor’s degree in Computer Science, Machine Learning, Statistics, Mathematics, or related quantitative field. 

Selenium (Software)

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, Communication, Complex Data Analysis, Conducting Research, Creativity, Customer Analysis, Customer Needs Analysis, Dashboard Creation, Data Analysis, Data Analysis Software, Data Collection, Data-Driven Insights, Data Integration, Data Integrity, Data Mining {+ 41 more}

Not Specified

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August 14, 2026