MLOps with AIML or GenAI engineervirtual drive

Please share updated CV, interviews will be as per below slots.  Need people having good project experience in genAI, MLops, model deployment and Python.

All locations. Fill below mandatory link.

GenAI-virtual interview with Capgemini--all locations, Sat 16th Nov 2025 Fill out form

MLops-virtual interview with Capgemini--all locations, Sat 16th Nov 2025 Fill out form

Ignore if filled.

10 am to 5 pm, 45 minutes interview duration, carry hard copy of Govt ID proof, join via laptop only.

Please go through JD and other attachment also. We need people having 6 plus years of experience.

Interview date: Saturday 16thNov 2025

Please be realistic on CTC and notice period. Documents should be in proper place.

Join interview invite via laptop only, carry hard copy of govt ID proof.

Regards

Asmita Gaur

Senior Consultant | Talent Acquisition

Capgemini Technology Services India | Noida

www.capgemini.com

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Interview duration : 45 minutes.

• Current CTC:
• Expected CTC:
• Notice period:
• Current and preferred location:
• Total and relevant exp:
• Current payroll company:
• Relevant exp in MLops only:

Interview will be virtual, share updated CV with us. Early joiners will be preferred. Interview will be of 45 minutes, with proper network.

MLOps Engineer

Your Role

• Design, implement, and maintain end-to-end ML pipelines for model training, evaluation, and deployment

• Collaborate with data scientists and software engineers to operationalize ML models, serving frameworks (TensorFlow Serving, TorchServe) and experience with MLOps tools

• Develop and maintain CI/CD pipelines for ML workflows

• Implement monitoring and logging solutions for ML models, experience with ML model serving frameworks (TensorFlow Serving, TorchServe)

• Optimize ML infrastructure for performance, scalability, and cost-efficiency

Your Profile

• Strong programming skills in Python (5+ years), with experience in ML frameworks; understanding of ML-specific testing and validation techniques

• Expertise in containerization technologies (Docker) and orchestration platforms (Kubernetes), Knowledge of data versioning and model versioning techniques

• Proficiency in cloud platform (AWS) and their ML-specific services with atleast 2-3 years of experience.

• Strong understanding of DevOps practices and tools (GitLab, Artifactory, Gitflow etc.)

• Experience with monitoring and observability tools (Prometheus, Grafana, ELK stack) and knowledge of distributed training techniques

What youll love about working here

• We recognise the significance of flexible work arrangements to provide support in hybrid mode, you will get an environment to maintain healthy work life balance

• Our focus will be your career growth & professional development to support you in exploring the world of opportunities.

• Equip yourself with valuable certifications & training programmes in the latest technologies such as MLOps, Machine Learning