Technical Lead - Data Science

City: Bengaluru

State/Province: Karnataka

Posting Start Date: 2/2/26

Wipro Limited (NYSE: WIT, BSE: 507685, NSE: WIPRO) is a leading technology services and consulting company focused on building innovative solutions that address clients' most complex digital transformation needs. Leveraging our holistic portfolio of capabilities in consulting, design, engineering, and operations, we help clients realize their boldest ambitions and build future-ready, sustainable businesses. With over 230,000 employees and business partners across 65 countries, we deliver on the promise of helping our customers, colleagues, and communities thrive in an ever-changing world. For additional information, visit us at www.wipro.com.

Job Description:

Job Description

Role Overview

Wipro Technologies invites applications for the position of Machine Learning Engineer (Python Coding with ML Experience) based in Bangalore. This role requires in-office commitment, working five days a week at the Wipro Kodathi ODC, ensuring dynamic collaboration within our high-performance teams.

We seek a dedicated professional with 6 to 10 years of experience to contribute to the full machine learning lifecycle. The ideal candidate will combine advanced software engineering capabilities with substantial machine learning expertise, leveraging Python and object-oriented programming principles. This role is central to delivering scalable, sustainable, and cutting-edge AI-powered solutions that empower our clients' digital transformation journeys.

Main Responsibilities

• Software Development: Craft clean, maintainable, and efficient Python code, adhering to best practices in OOP, ensuring modularity and extensibility across model management, evaluation metrics encapsulation, and controlled interfaces for model wrappers.
• End-to-End ML Pipeline Management: Develop, test, deploy, and monitor machine learning models and intelligent systems in production, focusing on robustness, scalability, and performance under real-world conditions.
• Architectural Design: Lead software design decisions applying best engineering principles to build modular, scalable ML pipelines, RESTful APIs, and microservices, contributing to evolving our ML platform architecture.
• Data Engineering: Design robust data pipelines supporting feature engineering, transformation, and versioning, enabling seamless integration for model training and online inference.
• ML Operations (MLOps): Implement automated CI/CD workflows, model testing, versioning, monitoring for drift and bias, and alerting mechanisms to ensure reliability and continuity of AI services in production.
• Performance Optimization: Identify bottlenecks and optimize ML systems for high throughput and latency-sensitive applications, ensuring scalability as workload demands grow.
• Documentation and Knowledge Sharing: Develop detailed technical documentation and collaborate within the team to facilitate knowledge transfer and maintain high-quality standards.

Educational & Professional Qualifications

• Master's degree in Computer Science, Machine Learning, Data Science, Electrical Engineering, or a closely related quantitative discipline.
• At least 5 years of progressive experience in machine learning engineering or software engineering roles with a strong ML focus.
• Advanced proficiency in Python for production-grade code; familiarity with ML frameworks such as TensorFlow, PyTorch, and Scikit-Learn.
• Sound knowledge of software design patterns, algorithms, data structures, object-oriented design, and experience with distributed systems.
• Experience working with SQL and NoSQL databases and managing large datasets efficiently.
• Demonstrated problem-solving skills with a methodical, pragmatic approach and effective communication to articulate complex ideas to diverse stakeholders.
• Desirable experience includes exposure to big data technologies like Spark, Hadoop, or Kafka and contributions to open-source ML projects.

Key Responsibilities and Initiatives

• Demand Generation and Solution Development Support
  • Collaborate closely with sales, pre-sales, and consulting teams to create innovative solutions and propositions that drive proactive demand generation and support go-to-market initiatives.
  • Lead the development of proofs of concept and prototype models aligned with strategic key offerings, propelling solution-led sales and customer engagement.
  • Establish partnerships with academic and research institutions to foster recruitment pipelines, participate in joint research initiatives, and contribute to data science educational programs.
• Revenue Generation and Solution Operationalization
  • Design and develop machine learning and deep learning models that deliver decision augmentation and automation capabilities across various business domains.
  • Work collaboratively with ML engineers, data engineers, and IT teams to evaluate deployment strategies and integration options for seamless ML solution delivery.
  • Integrate model performance management tools within existing enterprise infrastructure, ensuring continuous model health, reliability, and business alignment.
• Team Leadership and Management
  • Drive recruitment efforts to secure appropriate talent for the team, participating actively in candidate sourcing, interviewing, and onboarding processes.
  • Champion onboarding and continuous training programs to enhance team capability and effectiveness, fostering a culture of learning and development.
  • Manage employee retention and career progression, addressing attrition proactively and nurturing employee satisfaction.
  • Conduct regular performance reviews, provide constructive feedback, and act as a role model adhering to organizational leadership habits and standards.
  • Lead engagement initiatives that promote team morale, collaboration, and innovation in a supportive and inclusive workplace environment.

Performance Deliverables and Metrics
No. Performance Parameter Measurement Criteria 1 Demand Generation Order booking rates, pipeline growth attributable to solution development support 2 Revenue Generation via Delivery Excellence Timeliness of project delivery, documented customer success stories, and demonstrated use cases reflecting business impact 3 Capability Building and Team Management Percentage of team members trained on new critical skills, team attrition percentage, employee engagement survey scores

Essential Competencies

• Client Centricity: Consistently prioritize client needs and deliver solutions that generate superior value and satisfaction.
• Passion for Results: Demonstrate a strong drive to achieve excellence, surpass targets, and ensure impactful outcomes.
• Execution Excellence: Maintain an unwavering commitment to quality, agility, and timely delivery, adhering to robust processes.
• Collaborative Working: Foster effective teamwork across diverse functions, embracing inclusivity and shared success.
• Learning Agility: Continuously learn and adapt to emerging technologies, methodologies, and changing business landscapes.
• Problem Solving & Decision Making: Apply analytical thinking and data-driven approaches to resolve complex challenges effectively.
• Effective Communication: Clearly articulate complex technical concepts to both technical and non-technical stakeholders, ensuring shared understanding and engagement.

Mandatory Skills and Qualifications

• Proficiency in Python for Data Science with proven experience writing production-quality code aligned with industry best practices.
• Extensive experience (5-8 years) in machine learning engineering or related fields involving the design, development, and deployment of AI solutions.
• Hands-on familiarity with machine learning frameworks such as TensorFlow, Scikit-learn, and PyTorch.
• Strong foundation in software engineering, including object-oriented design, data structures, and algorithmic thinking.
• Experience in building and maintaining data pipelines, working with SQL and NoSQL databases, and managing data at scale.
• Demonstrated ability to lead technical projects and mentor team members.
• Preferred exposure to big data ecosystems (e.g., Spark, Hadoop, Kafka) and contributions to open-source communities are valuable assets.

About Wipro Technologies

Wipro is a global leader in information technology, consulting, and business process services, dedicated to harnessing innovation and technology to deliver transformative solutions. Our culture embodies reinvention, continuous learning, and a commitment to diversity and inclusion. Joining Wipro means becoming part of a purpose-driven organization that empowers talents to design their own career pathways while impacting industries worldwide with cutting-edge AI and data science solutions.

As the world evolves, so do we. We invite you to bring your expertise, curiosity, and passion to our collaborative teams and help shape the future.

Mandatory Skills: Python for Data Science .

Experience: 5-8 Years .

Reinvent your world. We are building a modern Wipro. We are an end-to-end digital transformation partner with the boldest ambitions. To realize them, we need people inspired by reinvention. Of yourself, your career, and your skills. We want to see the constant evolution of our business and our industry. It has always been in our DNA - as the world around us changes, so do we. Join a business powered by purpose and a place that empowers you to design your own reinvention.

Client-provided location(s): Bangalore, India

Job ID: Wipro-128184

Employment Type: OTHER

Posted: 2026-02-07T18:44:54