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Associate Process Manager

4-6 Years
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Job Description

Job Description: Python + Machine Learning Engineer

Experience: 48 Years (can be adjusted)
Location: Mumbai/Pune
Employment Type: Full-time

Role Overview

We are looking for a skilled Python + Machine Learning Engineer with hands-on experience in Generative AI, LLMs, and vector databases. The ideal candidate should be strong in ML fundamentals and capable of building scalable, production-ready solutions.

Key Responsibilities

  • Design, develop, and maintain robust applications using Python
  • Build and optimize Machine Learning models with a strong focus on performance and scalability
  • Work on Generative AI / Large Language Models (LLMs) use cases
  • Implement embeddings and semantic search solutions
  • Integrate and manage vector databases such as Elasticsearch, FAISS, or similar
  • Develop and maintain APIs using FastAPI or Flask
  • Perform data preprocessing, cleaning, and feature engineering
  • Collaborate with cross-functional teams to translate business requirements into technical solutions

Required Skills & Qualifications

  • Strong experience in Python development
  • Hands-on experience with Machine Learning fundamentals
  • Experience with Generative AI / LLMs
  • Practical exposure to vector databases (Elasticsearch, FAISS, etc.)
  • Strong understanding of embeddings and semantic search
  • Proficiency in Pandas, NumPy, Scikit-learn
  • Experience building RESTful APIs using FastAPI / Flask
  • Solid knowledge of data preprocessing and feature engineering techniques

Good to Have

  • Experience with cloud platforms (AWS/GCP/Azure)
  • Exposure to MLOps tools and model deployment
  • Familiarity with Docker/Kubernetes

More Info

About Company

eClerx provides business process management, automation and analytics services to a number of Fortune 2000 enterprises, including some of the world's leading financial services, communications, retail, fashion, media & entertainment, manufacturing, travel & leisure, and technology companies.

Job ID: 144622621

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