AI Engineer

“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. 

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.

Capco has a tolerant, open culture that values diversity, inclusivity, and creativity.

With no forced hierarchy at Capco, everyone has the opportunity to grow as we grow, taking their career into their own hands.

We believe that diversity of people and perspective gives us a competitive advantage.

Location - Pune

Experience - 5 to 10

Skills and Qualifications:

AI Engineer:

Key Responsiblities: 1. System Development: Designing and building AI models, such as neural networks, that learn from data and mimic human cognitive functions 2. Production Deployment: Transitioning research-level ML models into scalable, operational applications via APIs, microservices, or cloud platforms. 3. Data Handling & Training: Selecting, managing, and training models using large datasets, including natural language processing (NLP) and computer vision tasks. 4. Testing & Optimization: Evaluating accuracy, debugging, and improving AI performance to ensure systems run efficiently. 5. Collaboration: Working with data scientists and software engineers to align AI solutions with business objectives.

Required Skills and Qualifications: 1. Programming languages: Strong proficiency in Python, Java, or C++. How to use AI tooling to build up capability. Any UI/API automation framework. 2. ML Frameworks: Experience with TensorFlow, PyTorch, Keras, or Scikit-learn. How to use MCP server. 3. Data & Cloud Tools: Proficiency in SQL, Big Data Technologies, and cloud platforms like AWS SageMaker, Azure ML, or Google Cloud 4. Technical Skills: Expertise in machine learning, deep learning, NLP, computer vision, and algorithm development. 5. Education: Typically requires a Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field.