Senior Machine Learning Engineer

A Machine Learning (ML) Engineer job description typically outlines the need for a professional who can design, develop, and deploy scalable machine learning systems to solve business problems. This role sits at the intersection of data science and software engineering.

Here is a template structure for a Machine Learning Engineer Job Description, including typical responsibilities, required qualifications, and preferred skills:

Machine Learning Engineer Job Description Template

Role Summary

We are seeking a dedicated Machine Learning Engineer to join our team and contribute to cutting-edge AI projects. You will be responsible for building robust ML pipelines, designing and deploying machine learning models, and collaborating cross-functionally to integrate solutions that drive business impact.

Key Responsibilities

• Model Development and Implementation: Design, develop, and implement machine learning models (including deep learning architectures) using appropriate algorithms and tools to solve complex, data-driven challenges.
• Data Pipeline Construction: Build, maintain, and optimize data pipelines to ensure high-quality, efficient data flow for model training, validation, and serving.
• Model Optimization and Testing: Run comprehensive ML tests and experiments, perform statistical analysis, and fine-tune models (e.g., hyperparameter tuning) to maximize performance, accuracy, and efficiency.
• Production Deployment: Transition data science prototypes into production-ready, scalable, and reliable ML systems, and continuously monitor and maintain them.
• Collaboration: Work closely with data scientists, data engineers, and software engineers to translate business requirements into technical solutions and integrate ML models into existing applications.
• Research & Documentation: Stay abreast of the latest advancements in machine learning, AI, and relevant frameworks. Document all processes, methodologies, and test results.

Required Qualifications and Skills

• Education: Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, or a related quantitative field.
• Programming: High proficiency in a programming language essential for ML, such as Python, with experience in writing clean, robust, and scalable code.
• ML Expertise: Strong understanding of diverse machine learning algorithms (e.g., supervised, unsupervised, deep learning) and statistical methods.
• Frameworks & Libraries: Hands-on experience with major machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn, Keras).
• Core Computer Science: Solid understanding of computer science fundamentals, including data structures, algorithms, and software architecture.
• Data Handling: Experience with data preprocessing, feature engineering, and working with large, complex datasets.
• Problem-Solving: Excellent analytical, critical thinking, and problem-solving abilities.

Job Type: Full-time

Pay: ₹602,572.84 - ₹1,786,217.83 per year

Work Location: In person