Location: Hyderabad, India

Experience: 4 – 15 Years

Job ID: 389471

Role: Developer / MLOps Engineer

About the Company: A Global Leader in Technology

Join a premier global IT services and consulting organization recognized for its engineering excellence and commitment to digital transformation. With a presence in 55 countries, we empower industry-leading organizations to become “perpetually adaptive.” We provide a collaborative ecosystem where innovation meets scale, offering our employees the chance to work on the world’s most complex technology cycles.

The Role: DevOps Engineer (AI/ML Infrastructure)

We are seeking a seasoned DevOps Engineer with a deep specialization in Machine Learning Operations (MLOps). This role is not just about pipelines; it is about building the infrastructure that powers the next generation of Agentic AIand Generative AI solutions. You will bridge the gap between data science and production-grade software engineering.

Key Responsibilities

• MLOps Lifecycle: Design and maintain robust CI/CD pipelines for Supervised, Unsupervised, and Deep Learning models.

• Agentic Frameworks: Implement and scale Agentic AI frameworks such as LangGraph for complex autonomous workflows.

• Model Deployment: Deploy and monitor advanced algorithms including XGBoost, SVM, CNN, LSTM, and Isolation Forest for Anomaly Detection.

• GenAI Operations: Manage the infrastructure for LLM fine-tuning and multi-prompt design for enterprise-scale business applications.

• Cloud Infrastructure: Architect and manage cloud environments across Azure, AWS, or GCP, ensuring high availability for TensorFlow and other ML frameworks.

• Optimization: Implement Reinforcement Learning (RL) feedback loops into production environments to improve model performance over time.

Desired Candidate Profile

The ideal candidate is a hybrid expert who understands both the “Ops” of DevOps and the “Math” of Machine Learning.

Technical Skills Required

• Machine Learning: Strong foundation in Binary & Multiclass classification, Regression, and Deep Learning.

• Algorithms: Expertise in Isolation Forest, CNN, LSTM, and XGBoost.

• AI Frameworks: Hands-on experience with TensorFlow and Agentic AI (e.g., LangGraph).

• LLM Expertise: Proven experience in LLM fine-tuning and sophisticated prompt engineering.

• Programming: Advanced proficiency in Python for automation and modelling.

• Cloud: Competency in at least one major cloud provider (AWS/Azure/GCP).

Qualifications

• Education: Undergraduate degree in Computer Science, IT, or a related field.

• Experience: 4 to 15 years of professional experience in technology, with a focus on AI/ML integration.

Why Join Us?

• Work on high-impact Generative AI projects that redefine industries.

• A diverse and inclusive environment that promotes continuous learning.

• Competitive benefits and a clear path for professional advancement in the AI space.