Machine Learning Engineer ( Python Coding with ML Experience )

Location

Job Summary:

• We are seeking a highly skilled and versatile Machine Learning Engineer who embodies the rare combination of a strong software engineer and ML exposure with experience in designing, developing, and maintaining robust, scalable, and efficient software applications using Python, with a strong emphasis on Object-Oriented Programming principles to manage hyperparameters, encapsulate evaluation metrics, and create controlled interfaces for model wrappers
• You will be instrumental in designing, developing, deploying, and maintaining our core AI-powered products and features
• This demands a blend of analytical rigor, coding prowess, architectural foresight, and a deep understanding of the entire machine learning lifecycle, from data exploration and model development to deployment, monitoring, and continuous improvement

Key Responsibilities:

• Coding: Write clean, efficient, and well-documented Python code adhering to OOP principles (encapsulation, inheritance, polymorphism, abstraction)
• Experience with Python and related libraries (e.g, TensorFlow, PyTorch, Scikit-Learn)
• They are responsible for the entire ML pipeline, from data ingestion and preprocessing to model training, evaluation, and deploymentEnd-to-End ML Application Development: Design, development, and deployment of machine learning models and intelligent systems into production environments, ensuring they are robust, scalable, and performant
• Software Design & Architecture: Apply strong software engineering principles to design and build clean, modular, testable, and maintainable ML pipelines, APIs, and services
• Contribute significantly to the architectural decisions for our ML platform and applicationsData Engineering for ML: Design and implement data pipelines for feature engineering, data transformation, and data versioning to support ML model training and inferenceMLOps & Productionization: Establish and implement best practices for MLOps, including CI/CD for ML, automated testing, model versioning, monitoring (performance, drift, bias), and alerting systems for production ML models
• Performance & Scalability: Identify and resolve performance bottlenecks in ML systems
• Ensure the scalability and reliability of deployed models under varying load conditions
• Documentation: Create clear and comprehensive documentation for ML models, pipelines, and services

Required Qualifications

• Education: Masters degree in computer science, Machine Learning, Data Science, Electrical Engineering, or a related quantitative field
• Experience: 5+ years of professional experience in Machine Learning Engineering, Software Engineering with a strong ML focus, or a similar role
• Must have Programming Skills: Expert-level proficiency in Python, including experience with writing production-grade, clean, efficient, and well-documented code
• Experience with other languages (e.g, Java, Go, C++) is a plus
• Strong Software Engineering Fundamentals: Deep understanding of software design patterns, data structures, algorithms, object-oriented programming, and distributed systems
• Good to have Machine Learning Expertise:o Solid theoretical and practical understanding of various machine learning algorithmso Proficiency with ML frameworks such as PyTorch, Scikit-learn
• o Experience with feature engineering, model evaluation metrics, and hyperparameter tuningData Handling: Experience with SQL and NoSQL databases, data warehousing concepts, and processing large datasets
• Problem-Solving: Excellent analytical and problem-solving skills, with a pragmatic approach to delivering solutions
• Communication: Strong verbal and written communication skills, with the ability to explain complex technical concepts to both technical and non-technical audiences.

Preferred Qualifications:

• Experience with big data technologies (e.g., Spark, Hadoop, Kafka).
• Contributions to open-source projects or a strong portfolio of personal projects.