Description

Key Skills: Python, Machine Learning, PyTorch, TensorFlow, AWS, Docker, Kubernetes, MLOps

Good to Have Skills: R programming, Keras, Azure, Google Cloud Platform, Databricks, Apache Spark, Hive, Airflow, NLP, Optimization, CI/CD practices, Generative AI, LLMs, agent-based workflows

Roles & Responsibilities:

• Architect and build scalable ML systems leveraging optimization, NLP, and advanced analytics for supply chain solutions
• Lead end-to-end ML lifecycle including data pipelines, model training, deployment, and monitoring across production environments
• Provide technical leadership and mentorship to engineering and data science teams within the organization
• Build and maintain production-grade ML pipelines using CI/CD practices to ensure reliable deployment processes
• Optimize model performance, latency, and scalability while ensuring data security and governance standards are met
• Collaborate with product and business stakeholders to translate complex supply chain problems into ML-driven solutions
• Evaluate emerging technologies such as Generative AI, LLMs, and agent-based workflows for potential adoption

Experience Required: 8-10 years of experience in software engineering and machine learning, with 2+ years in a technical leadership role

Education: Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or related field

Key Skills

Education

Any Graduate