Machine Learning Engineer

Introduction

We are looking for a Machine Learning Engineer to design, build, and deploy scalable ML models and systems. You’ll work closely with data scientists, software engineers, and product teams to turn data into intelligent, production-ready solutions that drive real business impact.

Responsibilities

• Design, develop, and deploy machine learning models into production
• Build scalable ML pipelines for data preprocessing, training, evaluation, and inference
• Collaborate with data scientists to operationalize models
• Select appropriate algorithms and frameworks for different use cases
• Optimize model performance, accuracy, and efficiency
• Monitor deployed models and handle model drift and retraining
• Write clean, maintainable, and well-documented code
• Participate in code reviews and technical design discussions

Requirements

• Bachelor’s or Master’s degree in Computer Science, Data Science, AI, or related field (or equivalent experience)
• Strong programming skills in Python (preferred) or Java/Scala
• Solid understanding of machine learning algorithms and concepts
• Experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn
• Strong knowledge of data structures, algorithms, and software engineering fundamentals
• Experience building and consuming APIs
• Familiarity with SQL and NoSQL databases

• Experience with MLOps tools and practices
• Knowledge of cloud platforms (AWS, Google Cloud Platform, Azure)
• Experience with data processing frameworks (Spark, Hadoop)
• Understanding of deep learning, NLP, or computer vision
• Experience with Docker, Kubernetes, and CI/CD pipelines
• Exposure to model monitoring, versioning, and experiment tracking