Description

Key Skills: Machine Learning, Python, Pandas, NumPy, Scikit-learn, PyTorch, TensorFlow, SQL, Spark, Airflow, Feature Engineering, Model Evaluation, Statistics, ETL, REST API, gRPC, Microservices, Data Science.

Roles & Responsibilities:

• Design, develop, and deploy machine learning models for business applications.
• Build and maintain data pipelines and ETL workflows using Airflow or Spark.
• Perform data preparation, feature engineering, and data quality validation.
• Train, evaluate, and optimize machine learning models using industry best practices.
• Apply statistical techniques and experimentation to improve model performance.
• Work with large datasets using SQL and Python-based analytics tools.
• Integrate ML models into production systems through REST APIs or gRPC services.
• Collaborate with engineering and product teams to deliver end-to-end ML solutions.
• Monitor model performance and implement continuous improvements.
• Ensure scalability, reliability, and maintainability of ML solutions.
• Document models, experiments, and technical solutions.

Experience:

• 4-7 years of experience as an ML Engineer, Applied Scientist, or Data Scientist.
• Strong understanding of supervised and unsupervised machine learning techniques.
• Hands-on experience with Python, Pandas, NumPy, and Scikit-learn.
• Experience with PyTorch or TensorFlow for model development.
• Strong knowledge of feature engineering, model evaluation, and statistics.
• Experience building ETL pipelines using Spark or Airflow.
• Strong SQL skills for data extraction, transformation, and analysis.
• Experience deploying ML models using REST APIs, gRPC, and microservices.
• Experience working in production ML environments and end-to-end model lifecycle management.
• Strong analytical, problem-solving, and communication skills.

Education: B.Tech M.Tech (Dual), B.E., B.Tech

Key Skills

Education

Any Graduate