Job Description

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 , including typical responsibilities, required qualifications, and preferred skills:

Machine Learning Engineer 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