Sr. Machine Learning Engineer

Job Title: Sr. Machine Learning Engineer

Locations: Bangalore

Reports to: Director

A quick snapshot

As Sr. Machine Learning Engineer, you will Develop and optimize machine learning solutions by designing, implementing, and fine-tuning functionality for performance, scalability, and efficiency in production. The other responsibilities include data processing, feature engineering, developing, evaluating, and tuning models for optimal run-time performance.

Why its a big deal

This role is important as it balances technical implementation with project leadership, leading small to medium-sized initiatives while owning specific components in a Machine Learning solution.

Are you the person were looking for?

Experience. You must have more than 5 years of experience and atleast 2+ years of experience in data science, software development, or data engineering. You are also good in AI model development, training, scoring, and deployment

Optimization. You are good at ML solutions, especially in Machine Learning and optimizing it by designing (25%), implementing, and fine-tuning functionality for performance, scalability, and efficiency in production.

Collaboration. You are good in collaborate on integration and infrastructure by working with engineers to deploy modules, assist with platform upgrades, and enhance automated testing for reliability (25%)

Documentation. You know how to document and support development through detailed technical documentation to ensure clarity and continuity for future enhancement (25%)

Cross functional support. You provide technical support and training to Sales, Implementation, and Support teams

Participation. You will actively participate in code reviews, ensuring that code quality standards are met and that any issues are addressed promptly (10%)

Education. A bachelors degree in engineering or equivalent

Heres what will give you an edge

Proficiency. You are proficient in Python programming, Manage ML Libraries and TensorFlow, PyTorch, XgBoost, Scikit-learn, Spark ML and code/model versioning in Git, MLFlow.

Platforms. You have worked on Cloud computing platforms like Azure,databricks and know well to work on data analytics tool like Spark and Pandas.

Knowledge and understanding. You have good understanding of software testing, benchmarking, and continuous integration with experience in model management, data versioning, maintaining and orchestrating pipelines. You also know distributed computing and have knowledge of advanced machine learning and AI models such as Neural Network models.

Good to have. It is good if you demonstrate a strong understanding of core AI concepts, terminology, and practical applications. Regularly applies AI tools to improve task execution and decision-making, with growing awareness of ethical implications and responsible use.

Additional certification. Certifications in specialized areas like Natural Language Processing and Recommender systems Azure AI Engineer certification will be an added advantage.