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Job SummaryThe 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 ResponsibilitiesDesign, 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 optimise 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 productionise 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, optimise, 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 & Experience310 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 containerised deployments.Familiarity with Git and CI/CD practices.Strong debugging, analytical, and problem-solving skills.Preferred QualificationsBachelor'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 RequirementsExcellent 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. .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.