We are seeking a highly skilled Data Scientist with strong expertise in deep learning and proven experience in deploying machine learning models into production. The ideal candidate will have 2-5 years of experience in building, training, and scaling machine learning solutions, along with hands-on experience in modern ML tools and frameworks.

Key Responsibilities:

• Develop, optimize, and deploy deep learning models using TensorFlow and/or PyTorch.
• Design, implement, and evaluate machine learning models for various business applications.
• Collaborate with cross-functional teams to integrate machine learning solutions into production systems.
• Work with large datasets, and develop custom data pipelines using SQL and Python.
• Utilize multiprocessing and multithreading techniques for optimizing model training and performance.
• Leverage Azure cloud services to build scalable machine learning architectures.
• Manage and monitor ML experiments and model lifecycle using MLFlow.
• Perform data extraction, transformation, and loading (ETL) for analysis and model development.

Required Skills & Experience:

• 2-5 years of experience in data science or machine learning roles.
• Strong understanding of Machine Learning and Deep Learning models for classification, prediction and time series forecasting.
• Strong expertise in deep learning frameworks such as TensorFlow or PyTorch.
• Proficiency in SQL for managing and querying large datasets.
• Strong understanding of multiprocessing and multithreading in Python.
• Experience with cloud computing platforms, specifically Microsoft Azure.
• Hands-on experience in deploying machine learning models in production environments.
• Expertise in MLFlow for tracking experiments and managing machine learning pipelines.

Nice to Have:

• Familiarity with Azure Machine Learning (AML) or Databricks.
• Experience with Kubernetes or Docker for model deployment.
• Knowledge of data visualization tools like Power BI or Tableau.