Capgemini looking For Mlops engineer For Pune/Bangalore/Kolkata

Capgemini; Kolkata District, Pune District, Bengaluru; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Capgemini is seeking an MLOps Engineer to lead the design and implementation of scalable, secure, production-grade ML platforms across multi-cloud environments (Azure, AWS, GCP). You will drive end-to-end ML lifecycle solutions, ensuring reproducibility, governance, and operational excellence while collaborating with data science, platform engineering, and cloud teams.

Ideal candidates bring hands-on Kubernetes, Python, CI/CD, monitoring, and LLMOps experience to architect resilient ML systems

Qualifications

• overall experience and dedicated MLOps / AI Platform Engineering experience
• Kubernetes hands-on expertise
• Python development experience
• CI/CD implementation experience
• Monitoring and observability experience
• LLMOps implementation experience

Responsibilities

• Lead the design and implementation of scalable, secure, and production-grade ML platforms across multi-cloud environments (Azure, AWS, GCP).
• Architect end-to-end ML lifecycle solutions, enabling reproducibility, governance, and operational excellence with data science, platform engineering, and cloud teams.

Skills

MLOps / AI Platform Engineering

Kubernetes hands-on

Python development

CI/CD implementation

Monitoring and observability

LLMOps implementation

Job description

Role & responsibilities

MLOps Engineer to lead the design and implementation of scalable, secure, and production-grade ML platforms across multi-cloud environments (Azure, AWS, GCP).

The role involves architecting end-to-end ML lifecycle solutions, enabling reproducibility, governance, and operational excellence while working closely with data science, platform engineering, and cloud teams.

Preferred candidate profile

1. overall experience and dedicated MLOps / AI Platform Engineering experience


2. Kubernetes hands-on expertise


3. Python development experience


4. CI/CD implementation experience


5. Monitoring and observability experience


6. LLMOps implementation experience