#18051-AI/ML Engineer

Key Responsibilities

• Design, develop, and deploy ML models and AI solutions across various domains such as NLP, computer vision, recommendation systems, time-series forecasting, etc.

• Perform data preprocessing, feature engineering, and model training using frameworks like TensorFlow, PyTorch, Scikit-learn, or similar.

• Collaborate with cross-functional teams to understand business problems and translate them into AI/ML solutions.

• Optimize models for performance, scalability, and reliability in production environments.

• Integrate ML pipelines with production systems using tools like MLflow, Airflow, Docker, or Kubernetes.

• Conduct rigorous model evaluation using metrics and validation techniques.

• Stay up-to-date with state-of-the-art AI/ML research and apply findings to enhance existing systems.

• Mentor junior engineers and contribute to best practices in ML engineering.

Required Skills & Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field.

• 4–8 years of hands-on experience in machine learning, deep learning, or applied AI.

• Proficiency in Python and ML libraries/frameworks (e.g., Scikit-learn, TensorFlow, PyTorch, XGBoost).

• Experience with data wrangling tools (Pandas, NumPy) and SQL/NoSQL databases.

• Familiarity with cloud platforms (AWS, GCP, or Azure) and ML tools (SageMaker, Vertex AI, etc.).

• Solid understanding of model deployment, monitoring, and CI/CD pipelines.

• Strong problem-solving skills and the ability to communicate technical concepts clearly.