Key Responsibilities

• Design, train, and deploy machine learning and deep learning models for production use
• Build and maintain ML pipelines for data preprocessing, model training, evaluation, and deployment
• Apply NLP, computer vision, or predictive analytics techniques as per project requirements
• Collaborate with data engineers to ensure clean, well-structured training data
• Monitor model performance and implement retraining strategies as needed
• Research and evaluate emerging AI/ML frameworks and techniques
• Present findings and model insights to technical and non-technical stakeholders

Requirements

• 5–10+ years of experience in AI/ML engineering or data science
• Strong proficiency in Python and ML frameworks such as TensorFlow, PyTorch, or scikit-learn
• Experience deploying ML models on cloud platforms (AWS SageMaker, Azure ML, or GCP Vertex AI)
• Knowledge of NLP techniques, transformers, and LLMs is highly desirable
• Familiarity with MLOps practices and tools (MLflow, Kubeflow, etc.)
• Strong mathematical foundation in statistics, linear algebra, and probability
• Experience with big data tools (Spark, Hadoop) is a plus

Skills Required