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Machine Learning Engineer Job Description Job Summary We are looking for a talented and motivated Machine Learning Engineer with 3–6 years of hands-on experience in developing, deploying, and maintaining Machine Learning and Deep Learning solutions. The ideal candidate should have strong knowledge of ML algorithms, model development, data preprocessing, model evaluation, and production deployment. Experience with MLflow , SQL , and modern ML development practices is essential. Key Responsibilities * Design, develop, train, and deploy Machine Learning and Deep Learning models for business use cases. * Build end-to-end ML pipelines, including data collection, preprocessing, feature engineering, model training, validation, and deployment. * Develop scalable and production-ready machine learning solutions. * Perform model evaluation, hyperparameter tuning, and performance optimization. * Implement experiment tracking, model versioning, and model lifecycle management using MLflow . * Work with structured and semi-structured datasets. * Create reusable ML components and automation pipelines. * Collaborate with cross-functional teams to understand business requirements and translate them into AI solutions. * Monitor deployed models and improve model performance over time. * Document model architecture, assumptions, and deployment processes. * Stay updated with the latest advancements in Machine Learning, Deep Learning, and Generative AI technologies. Required Skills Machine Learning * Strong understanding of supervised and unsupervised learning algorithms. * Experience with classification, regression, clustering, anomaly detection. * Feature engineering and feature selection techniques. * Model evaluation metrics and validation strategies. * Hyperparameter tuning and optimization. * Model interpretability and explainability. Deep Learning * Good understanding of neural networks and deep learning architectures. * Hands-on experience with Transformer-based architectures (preferred) * Experience using TensorFlow, Keras, or PyTorch. Programming * Strong proficiency in Python. * Experience with NumPy, Pandas, Scikit-learn, Matplotlib, and related ML libraries. * Knowledge of object-oriented programming and software engineering best practices. SQL * Strong SQL skills. * Experience writing complex queries, joins, aggregations, subqueries, and performance optimization. * Ability to work with relational databases efficiently. MLflow * Hands-on experience with MLflow. * Experiment tracking. * Model registry. * Model versioning. * Model deployment. * Reproducible ML workflows. Preferred Skills * Experience with cloud platforms such Azure. * Knowledge of Docker and containerized ML deployments. * Experience with REST API development using Flask or FastAPI. * Familiarity with Git and CI/CD pipelines. * Exposure to MLOps concepts and deployment best practices. * Understanding of distributed data processing using Spark is a plus. * Exposure to Large Language Models (LLMs), Generative AI is an added advantage. *Hands-on experience with Evidently AI for model monitoring, data quality validation, drift detection, and performance reporting. *Experience using automated code quality and code review tools such as SonarQube, CodeClimate, or similar platforms to ensure code quality, maintainability, and adherence to best practices.
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.