Data Scientist - Machine Learning

Talent Corner Hr Services; Chakan; On-site; INR 1,200,000 - 1,900,000; Full time

Job summary

Talent Corner Hr Services is seeking an experienced ML engineer to develop, train, and deploy machine learning and deep learning models. The role involves data preprocessing, feature engineering, hyperparameter tuning, and building end-to-end ML pipelines.

You will integrate models into applications via Python APIs (FastAPI/Flask) and work with large datasets using Python and SQL. The ideal candidate has strong Python/SQL skills, hands-on experience with ML algorithms (regression,

Qualifications

• Strong proficiency in Python and SQL for data processing and model development.
• Hands-on experience with ML algorithms including regression, classification, clustering, and ensemble methods.
• Experience with Scikit-learn, Pandas, and NumPy for data manipulation and modeling.
• Good understanding of model evaluation, feature engineering, and hyperparameter tuning.
• Experience building and deploying production-grade ML solutions.

Responsibilities

• Develop, train, and deploy ML and DL models.
• Perform data preprocessing, feature engineering, and hyperparameter tuning.
• Build and optimize end-to-end ML pipelines.
• Integrate ML models into applications using Python APIs (FastAPI/Flask).
• Work with large datasets using Python and SQL.
• Evaluate, monitor, and improve model performance in production.
• Collaborate with cross-functional teams to integrate AI solutions.
• Contribute to GenAI/LLM-based projects where applicable.

Skills

Python

SQL

ML Algorithms

Pandas

NumPy

Scikit-learn

TensorFlow

PyTorch

Model evaluation

Tools

FastAPI

Flask

Job description

Role & responsibilities

• Develop, train, and deploy Machine Learning and Deep Learning models.
• Perform data preprocessing, feature engineering, feature selection, and hyperparameter tuning.
• Build and optimize end-to-end ML pipelines.
• Integrate ML models into applications using Python APIs (FastAPI/Flask).
• Work with large datasets using Python and SQL.
• Evaluate, monitor, and improve model performance in production.
• Collaborate with cross-functional teams to integrate AI solutions.
• Contribute to GenAI/LLM-based projects where applicable.

Preferred candidate profile

• Strong proficiency in Python and SQL.
• Experience with Machine Learning algorithms including Regression, Classification, Clustering, Random Forest, XGBoost, and LightGBM.
• Hands-on experience with Scikit-learn, Pandas, and NumPy.
• Good understanding of model evaluation, feature engineering, and hyperparameter tuning.
• Experience building and deploying production-grade ML solutions.
• Basic knowledge of TensorFlow or PyTorch is a plus.