If you’re a seasoned professional in Machine Learning, Infosys is calling you! The tech giant is hiring Machine Learning Engineers across Hyderabad, Pune, and Bengaluru with a hybrid work setup. This is your chance to join one of India’s top IT services firms and work on cutting-edge AI and MLOps projects.
With 5 openings available and over 100 applicants already, here’s everything you need to know to apply successfully.
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📌 Job Highlights – Machine Learning Engineer at Infosys
| Locations | Hyderabad, Pune, Bengaluru (Hybrid) |
| Company | Infosys |
| Role | Machine Learning Engineer |
| Posted | 4 days ago |
| Openings | 5 |
| Experience | 2-3 years |
| Salary | Not Disclosed |
| Employment Type | Full Time, Permanent |
| Apply Mode | Register/Login to Apply |
💡 Why Join Infosys as a Machine Learning Engineer?
As a Machine Learning Engineer at Infosys, you’ll work on impactful MLOps solutions for global clients. From operationalizing ML models to setting up coding standards and pipelines, this role gives you the opportunity to grow in a challenging and rewarding environment.
Infosys’s focus on Generative AI, Deep Learning, and Cloud Technologies makes this a dream opportunity for those passionate about AI innovations.
📋 Roles & Responsibilities
- Understand business requirements and translate them into technical specifications.
- Deliver successful MLOps solutions in client consulting environments.
- Define key business problems, develop and analyze solutions, and present to clients.
- Build and manage ML Pipelines from creation to execution.
- Guide teams to resolve pipeline failures and debug issues.
- Engage with stakeholders for progress updates.
- Research emerging topics and enhancements in Cloud Technologies.
🎓 Eligibility & Preferred Skills
- Education: UG – Any Graduate, PG – Any Postgraduate
- Experience: 6–10 years in Data Science & Analytics
- Preferred Skills:
- Data Science, Machine Learning, Python, Generative AI
- Deep Learning, Pytest frameworks, REST APIs
- Agile methodology, JIRA tracking
- Domain expertise in Retail, CPG, Logistics is a plus.
Why MLOps Roles Are Highly Demanded in 2025
Machine Learning Operations (MLOps) has emerged as one of the fastest-growing fields in data science. With the increasing adoption of AI across industries, companies are looking for experts who can deploy, monitor, and manage ML models at scale.
Infosys, with its global client base, is focusing heavily on building robust MLOps pipelines to ensure AI models are production-ready and deliver consistent business value.
This demand creates excellent career prospects for engineers skilled in MLOps and cloud technologies. Professionals in this role often move into leadership positions such as AI Project Managers or Chief Data Scientists.
Tips for Applicants to Stand Out
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Highlight experience with MLOps tools like Kubernetes, Docker, or MLflow.
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Showcase projects where you operationalized ML models in real-world environments.
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Demonstrate knowledge of cloud platforms like AWS, Azure, or GCP.
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Be ready to discuss your contributions in team settings and client-facing situations.
📝 How to Apply for Infosys Machine Learning Engineer Role?
- Step 1: Visit the official Infosys careers portal.
- Step 2: Register or login to your account.
- Step 3: Upload your updated CV and complete the application form.
- Step 4: Keep an eye on your email for further interview steps.
Apply Now on Infosys Careers Portal – https://www.infosys.com/careers.html
📈 Why Infosys?
With 3.6+ lakh employees globally and a reputation for technological innovation, Infosys provides unparalleled career growth, international exposure, and access to state-of-the-art projects in AI, cloud, and analytics.
This role may involve extensive travel and a mix of remote and in-office work, ensuring flexibility and global client interaction.
🕒 Don’t Miss Out – Apply Soon!
With over 100 applicants already and limited openings (just 5), act fast to secure your spot in Infosys’s elite Machine Learning team.
Conclusion
This Machine Learning Engineer role at Infosys is an excellent opportunity for professionals looking to advance their careers in data science and MLOps. With limited openings and high competition, apply early to secure your position.
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