Description

Key Responsibilities

• Design, build, deploy, and maintain ML models and end-to-end ML pipelines.
• Perform data preparation, feature engineering, model training, evaluation, and optimization.
• Deploy and monitor models in production, including model drift detection and retraining.
• Collaborate with data engineering, DevOps, and business teams to deliver scalable ML solutions.
• Architect enterprise-scale ML systems and drive MLOps, automation, governance, and reliability initiatives.
• Mentor engineers, provide technical leadership, and evaluate emerging AI/ML technologies.

Required Skills

• Strong Python expertise with NumPy, Pandas, Scikit-learn.
• Hands-on experience with TensorFlow and/or PyTorch.
• Experience building and deploying ML solutions on AWS, Azure, or GCP.
• Knowledge of ML pipelines, model evaluation, CI/CD, version control, and MLOps practices.
• Strong understanding of ML system design, performance optimization, and monitoring.

Preferred Skills

• Experience with MLflow, SageMaker, Azure ML or similar MLOps platforms.
• Knowledge of Docker, Kubernetes, Spark, or Ray.
• Experience with LLMs, Deep Learning, Transformers, Vector Databases, and ML Governance.
• Prior experience leading ML projects or mentoring teams

Key Skills

Education

Bachelor's degree