Machine Learning Engineer JD

• Design, develop, and implement machine learning models for classification, regression, NLP, recommendation systems, or computer vision tasks.

• Perform data preprocessing, feature engineering, and exploratory data analysis (EDA) to prepare datasets for modeling.

• Develop ML pipelines and integrate models into production environments using APIs or cloud services.

• Optimize and fine-tune models for accuracy, efficiency, and scalability.

• Collaborate with data engineers, software developers, and business stakeholders to define requirements and deliver AI-driven solutions.

• Monitor model performance and retrain/update models as necessary.

• Document workflows, models, and processes to ensure reproducibility and knowledge sharing.

Required Technical Skills :

• Programming Languages : Python (primary), R or Java (optional).

• ML Frameworks : TensorFlow, PyTorch, scikit-learn, Keras.

• Data Manipulation & Analysis : Pandas, NumPy, Matplotlib, Seaborn.

• Databases : SQL, NoSQL (MongoDB, Cassandra, or equivalent).

• Deployment & Cloud : AWS SageMaker, Azure ML, or GCP AI Platform.

• Algorithms : Supervised and unsupervised learning, NLP, deep learning, and reinforcement learning basics.

• Tools : Git, Jupyter Notebooks, Docker, and CI/CD pipelines for ML.