Python/ML Engineer

Job Summary

The Python/ML Engineer is responsible for designing, developing, and deploying scalable AI-powered applications using Python, Machine Learning, and Generative AI technologies. The role focuses on backend development, productionizing ML models, building APIs and microservices, developing RAG pipelines, integrating Large Language Models (LLMs), and delivering enterprise AI solutions that are secure, scalable, and production-ready.

Key Responsibilities

• Design, develop, and maintain scalable backend applications using Python.
  Build REST APIs and microservices to expose Machine Learning and Generative AI capabilities.
• Develop, integrate, and deploy Machine Learning models into production environments.
• Build and optimize Retrieval Augmented Generation (RAG) pipelines and AI orchestration workflows.
• Work with Large Language Models (LLMs) and Generative AI frameworks to develop enterprise AI applications.
• Design efficient data processing pipelines for model training and inference.
• Build secure, reliable, and high-performance backend services.
• Collaborate with Data Scientists and AI Engineers to productionize ML models and improve inference performance.
• Develop reusable, maintainable, and well-tested code following software engineering best practices.
• Participate in solution architecture discussions and technical design decisions.
• Monitor, troubleshoot, optimize, and maintain deployed AI applications.
• Collaborate with internal teams and customer stakeholders to understand business requirements and deliver technical solutions.
• Participate in code reviews and mentor junior developers when required.

Required Skills & Experience

• 3–10 years of experience in Python Development and Machine Learning.
• Strong proficiency in Python programming.
• Strong understanding of Object-Oriented Programming (OOP), Design Patterns, and Clean Coding principles.
• Hands-on experience with FastAPI or Flask frameworks.
• Experience developing REST APIs and distributed backend systems.
• Strong knowledge of SQL and relational databases.
• Good understanding of Data Structures, Algorithms, and Software Design principles.
• Hands-on experience with Machine Learning frameworks such as PyTorch or TensorFlow.
• Experience deploying and maintaining Machine Learning models in production environments.
• Good understanding of model serving, inference pipelines, and production monitoring.
• Experience with Docker and containerized deployments.
• Familiarity with Git and CI/CD practices.
• Strong debugging, analytical, and problem-solving skills.

Preferred Qualifications

• Bachelor’s degree in Computer Science, Engineering, or a related field.
• Experience with Microsoft Azure and Azure Machine Learning.
• Exposure to OpenAI, Azure OpenAI, or open-source Large Language Models (LLMs).
• Experience building Retrieval Augmented Generation (RAG) solutions.
• Knowledge of LangChain, LangGraph, or similar AI orchestration frameworks.
• Experience with vector databases and semantic search technologies.
• Familiarity with Kafka, RabbitMQ, or Azure Service Bus.
• Exposure to Kubernetes and cloud-native deployments.
• Experience working in Agile development environments.

Other Requirements

• Excellent communication and interpersonal skills.
• Self-motivated with the ability to work independently and collaboratively.
• Ability to coordinate effectively with onsite and offshore teams.
• Proactive problem-solving mindset with strong ownership and accountability.