Senior Machine Learning Engineer
2 days ago
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, ₹1,786,217.83 per year
Work Location: In person
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