AI/MLEngineer

Design, develop, and deploy ML models for predictive analytics, computer vision, or NLP use cases. Build scalable data ingestion and preprocessing pipelines using Python (Pandas, PySpark, etc.). Implement and optimize ML workflows using frameworks like TensorFlow, PyTorch, or scikit-learn. Collaborate with data engineers and data scientists to integrate models into production systems. Automate model retraining, monitoring, and performance tracking.

Must Have

• Design, develop, and deploy ML models for predictive analytics, computer vision, or NLP use cases
• Build scalable data ingestion and preprocessing pipelines using Python
• Implement and optimize ML workflows using frameworks like TensorFlow, PyTorch, or scikit-learn
• Collaborate with data engineers and data scientists to integrate models into production systems
• Automate model retraining, monitoring, and performance tracking
• Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field
• 4-9 years of hands-on experience in Python-based AI/ML development
• Proficiency with Python libraries such as NumPy, Pandas, scikit-learn, TensorFlow, PyTorch, and MLflow
• Experience with data processing frameworks such as PySpark or Dask
• Familiarity with cloud platforms (AWS, Azure, GCP) and containerization tools (Docker, Kubernetes)
• Experience with API integration and MLOps tools (Databricks, Airflow, SageMaker)
• Understanding of version control (Git) and CI/CD pipelines

Good to Have

• Understanding of machine learning algorithms, model evaluation, and feature engineering

Key Responsibilities

• Design, develop, and deploy ML models for predictive analytics, computer vision, or NLP use cases.
• Build scalable data ingestion and preprocessing pipelines using Python (Pandas, PySpark, etc.).
• Implement and optimize ML workflows using frameworks like TensorFlow, PyTorch, or scikit-learn.
• Collaborate with data engineers and data scientists to integrate models into production systems.
• Automate model retraining, monitoring, and performance tracking.

Required Skills & Qualifications

• Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field.
• 4-9 years of hands-on experience in Python-based AI/ML development.
• Good to have understanding of machine learning algorithms, model evaluation, and feature engineering.
• Proficiency with Python libraries such as NumPy, Pandas, scikit-learn, TensorFlow, PyTorch, and MLflow.
• Experience with data processing frameworks such as PySpark or Dask.
• Familiarity with cloud platforms (AWS, Azure, GCP) and containerization tools (Docker, Kubernetes).
• Experience with API integration and MLOps tools (Databricks, Airflow, SageMaker, etc.).
• Understanding of version control (Git) and CI/CD pipelines