Description

Design, build, and maintain enterprise-scale ML systems and end-to-end pipelines.

This role is on-site.

Responsibilities

• Architect scalable ML solutions and drive MLOps, automation, and governance initiatives.
• Perform data preparation, feature engineering, model training, evaluation, and optimization.
• Deploy models to production and implement monitoring for drift detection and retraining.
• Mentor engineers and provide technical leadership on emerging AI/ML technologies.

Required Skills

• 10+ years of experience with strong Python expertise (NumPy, Pandas, Scikit-learn).
• Hands-on experience with TensorFlow and/or PyTorch.
• Proven track record building and deploying ML solutions on AWS, Azure, or GCP.
• Deep knowledge of ML pipelines, 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.

Key Skills

Education

Bachelor's degree