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MLOPs Engineer @ Capgemini

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 MLOPs Engineer

Job Description

Must-Have Skills

Core competencies required to fulfill the role:

Deep NLP Expertise

Hugging Face Transformers (BERT, GPT, etc.)

NLTK

Knowledge Graphs & Semantic Search

AI/ML Frameworks

PyTorch, TensorFlow, Keras

Python Programming (for NLP and ML model development)

Model Deployment & Optimization

Building production-ready NLP solutions

Good-to-Have Skills

Enhances capability and accelerates innovation:

Generative AI & LLM Fine-Tuning

Prompt engineering, RAG (Retrieval-Augmented Generation)

API Development

RESTful APIs for NLP services

MLOps Practices

Model versioning, monitoring, retraining pipelines

Cloud Platforms

GCP or Azure for scalable NLP deployments

Distributed & Parallel Processing

Ability to design and optimize algorithms for large-scale NLP tasks

CI/CD for NLP Pipelines

Jenkins, GitHub Actions for ML workflows

Trainable Skills (COE Enablement)

Skills that can be developed internally:

Performance Optimization

Model compression, quantization for faster inference

Containerization

Docker, Kubernetes for NLP model deployment

Job Classification

Industry: IT Services & Consulting
Functional Area / Department: Engineering - Software & QA
Role Category: Software Development
Role: Software Development - Other
Employement Type: Full time

Contact Details:

Company: Capgemini
Location(s): Pune

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Keyskills:   Huggingface NLP MLOPs Aiml Transformers RAG

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Capgemini

Company DetailsCapgemini UAT