Ekfrazo Technologies - NLP Engineer - Machine Learning Solutions

EKFRAZO TECHNOLOGIES PRIVATE LIMITED

Bangalore

4 - 8 Years

27+ Reviews

NLP Azure Machine Learning AI Integration Python PyTorch Tensorflow Data Engineering

Posted on: 20/08/2025

Job Description

About the Role :

We are seeking an experienced NLP Engineer with strong expertise in Azure Machine Learning to design, develop, fine-tune, and deploy NLP solutions for logistics and supply chain workflows.

The ideal candidate will have hands-on expertise in Hugging Face, spaCy, and Azure services, with proven experience in deploying scalable machine learning models in production environments.

Key Responsibilities (KRA) :

- Develop, fine-tune, and optimize NLP models for text classification, entity extraction, and intent detection using Hugging Face and spaCy.

- Build and deploy machine learning solutions on Azure ML and Azure Kubernetes Service (AKS) ensuring scalability, high availability, and low latency.

- Design and implement models for SKU classification, anomaly detection, and automated routing in logistics workflows.

- Develop data ingestion, preprocessing, and transformation pipelines integrating with APIs, warehouse management systems, and image recognition outputs.

- Monitor, evaluate, and retrain models using feedback loops, drift detection, and performance tracking via Azure Application Insights.

- Collaborate with cross-functional teams to integrate AI/ML capabilities into logistics operations and improve decision-making.

- Maintain best practices for MLOps, CI/CD pipelines, and automated deployments on Azure.

- Conduct research and stay updated on emerging NLP, Azure ML, and cloud-based AI innovations to continuously improve solutions.

Required Skills & Qualifications :

- Proven experience (4 to 8 years) in Natural Language Processing (NLP) and Machine Learning.

- Strong expertise in Hugging Face Transformers and spaCy for NLP tasks.

- Hands-on experience with Azure Machine Learning for training, deployment, and lifecycle management of ML models.

- Experience deploying and scaling ML workloads on Azure Kubernetes Service (AKS).

- Proficiency in Python and ML frameworks (PyTorch, TensorFlow, or equivalent).

- Experience with data engineering workflows, API integrations, and preprocessing unstructured text data