Description

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

Good to Have Skills: R programming, Keras, Google Cloud Platform, Databricks, Apache Spark, Hive, Airflow, MLOps practices, CI/CD, Natural Language Processing, optimization algorithms, Generative AI, Large Language Models, agent-based workflows, data engineering, system design, and technical leadership experience.

Roles & Responsibilities:

• Architect and build scalable machine learning systems leveraging optimization, natural language processing, and advanced analytics.
• Lead end-to-end machine learning lifecycle including data pipelines, model training, deployment, and monitoring.
• Provide technical leadership and mentorship to engineering and data science teams across the organization.
• Build and maintain production-grade machine learning pipelines using continuous integration and continuous deployment practices.
• Optimize model performance, latency, and scalability while ensuring data security and governance requirements.
• Collaborate with product and business stakeholders to translate complex problems into machine learning-driven solutions.
• Evaluate emerging technologies such as Generative AI, Large Language Models, and agent-based workflows for adoption.
• Partner with Supply Chain Planning and Technology teams to drive advanced analytics and AI-led decisioning.

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 (or equivalent combination of education and experience)

Key Skills

Education

Any Graduate