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Location: India - Bengaluru; India - Chennai; India - Gurugram; India - Hyderabad; India - Mumbai; India - Pune
Department: Data & Analytics
Job Title: ML AI Platform Engineer
About Us
“Capco, a Wipro company, is a global technology and management consulting firm. Awarded with Consultancy of the year in the British Bank Award and has been ranked Top 100 Best Companies for Women in India 2022 by Avtar & Seramount. With our presence across 32 cities across globe, we support 100+ clients across banking, financial and Energy sectors. We are recognized for our deep transformation execution and delivery.
WHY JOIN CAPCO?
You will work on engaging projects with the largest international and local banks, insurance companies, payment service providers and other key players in the industry. The projects that will transform the financial services industry.
MAKE AN IMPACT
Innovative thinking, delivery excellence and thought leadership to help our clients transform their business. Together with our clients and industry partners, we deliver disruptive work that is changing energy and financial services.
#BEYOURSELFATWORK
Capco has a tolerant, open culture that values diversity, inclusivity, and creativity.
CAREER ADVANCEMENT
With no forced hierarchy at Capco, everyone has the opportunity to grow as we grow, taking their career into their own hands.
DIVERSITY & INCLUSION
We believe that diversity of people and perspective gives us a competitive advantage.
Job Title: ML AI Platform Engineer
Location: Pune/ Bengaluru/ Mumbai/ Hyderabad/ Gurugram/ Chennai (Hybrid - 2 days a week from office)
Experience: Min 5yrs in Python development
Role – An Engineer in ML Platform team, will support resolve customer issues , respond to query, perform monthly RCA, identify improvement actions and ensure smooth experience for the customer, minimize issues regularly from the platform. An Engineer in ML Platform team, will understand industry trends , design, enhance, and improve/optimize ML platform solutions for model training and agent development.
Visa has an internal platform similar in purpose to parts of Google Vertex AI or Amazon SageMaker. Visa’s ML developers use this platform to train models, run experiments, execute AI workloads, and develop agents. This engineer works on the platform that enables those activities.
Technical Skills Skill Expectation Python Very strong hands-on development skills, including debugging, performance optimization, and backend/system-level programming Tensor Computing Good understanding of tensors, tensor operations, memory layout, and execution fundamentals Distributed Systems Hands-on experience with at least one distributed computing framework such as Apache Spark or Ray Systems Engineering Strong understanding of operating systems, processes, threads, memory management, concurrency, and parallel computing Compute Architecture Understanding of CPU, GPU, and AI accelerator fundamentals, including how compute workloads use hardware resources
Most IT Jobs posts in Gurgaon ask for 3–6 years of experience (41% of 454 that say).
From live job posts on CoreHRx, updated 10 Nov 2026. Skill figures count posts that list their skills; salary figures only posts that show a salary.
The post does not state the pay. As an estimate, comparable posts on CoreHRx advertise ₹10L – ₹24L a year (typical for IT Jobs in India, 810 posts).
The post asks for 5 Yrs experience.
In Gurgaon, Mumbai, Pune, Hyderabad, Bangalore (hybrid).
It is a full time job.
Interview preparation · 60 questions
This page helps Indian job seekers prepare for Python interviews for backend, data engineering and data analyst roles, whether you are a fresher facing your first technical round or an experienced developer aiming for a senior position. It has 60 questions in three levels, easy, medium and hard, each with a concise sample answer and, where it helps, runnable Python 3.12 code. Topics include data structures, OOP, generators, decorators, the GIL and concurrency, type hints, testing and performance. Answer each question aloud in your own words first, then compare with the sample answer and run the code to check your understanding.
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