KPMG Recruitment 2026 – Associate Consultant/Consultant

KPMG

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1–6 Years4 days ago

Experience1–6 Years

QualificationB.E / B.Tech / M.E / M.Tech

Key Responsibilities

The role also includes building and maintaining scalable data ingestion and ETL pipelines. AI applications often require information from multiple structured and unstructured sources.
REST APIs can be used to acquire and integrate information from internal and external systems. Candidates should understand API requests, authentication, response handling, errors, and integration patterns.
Tools such as BeautifulSoup (BS4) and Selenium are mentioned for data acquisition and enrichment. Candidates should understand responsible scraping and reliable extraction workflows.
Data used by enterprise AI systems needs to be accurate, consistent, traceable, and appropriately governed. The role therefore includes responsibility for data quality and governance.
The position is also research-oriented. Candidates may need to study research papers, technical publications, and open-source repositories to identify useful emerging AI capabilities.
They may also prototype new LLMs, OCR technologies, document intelligence platforms, and foundation models before recommending practical solutions for business problems.

Skills & Eligibility

Candidates applying for the Associate Consultant/Consultant role should possess a B.E, B.Tech, M.E, or M.Tech qualification in a relevant field.
The experience requirement is 1–6 years. Because the position involves production-grade AI engineering, candidates should have practical professional experience rather than only academic exposure to machine learning or generative AI.
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B.E/B.Tech/M.E/M.Tech in a relevant field.
1–6 years of relevant experience.
Strong hands-on Python programming experience.
Experience building modular, scalable, maintainable, and production-grade AI applications.
Experience with Generative AI and Agentic AI technologies.
Understanding of RAG, GraphRAG, vector databases, and semantic search.
Experience with AI model optimization and secure enterprise deployment.
Python is the core programming language for this position. KPMG expects candidates to have strong hands-on experience rather than basic scripting knowledge.
Professionals should be comfortable building modular Python applications, integrating APIs, processing data, developing AI workflows, exposing services, writing maintainable code, and supporting production deployments.
The role also mentions several Python-based technologies and libraries including Pandas, Polars, PyTorch, FastAPI, and Streamlit.
Pandas is relevant for data manipulation and analysis. Candidates should understand dataframes, filtering, transformations, joins, aggregation, missing-data handling, and efficient data processing.
Polars is a high-performance dataframe library that can be useful for processing larger datasets efficiently. Experience with Polars is specifically listed as a mandatory skill.
PyTorch is important for machine learning and deep learning workflows. Candidates should understand tensors, models, inference, training fundamentals, and model execution where applicable.
FastAPI is relevant for exposing AI capabilities through production-ready APIs. Candidates should understand endpoint design, request validation, authentication concepts, asynchronous APIs, and service integration.
Streamlit can be used to create interactive interfaces for data and AI applications. Candidates should understand how to build simple user-facing AI tools and prototypes using the framework.
Candidates should possess a B.E, B.Tech, M.E, or M.Tech degree in a relevant field.

Note: This job is posted on external sites. Joblit shares the listing for convenience and does not take responsibility for third-party content.

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