Description

You will lead the architectural design and implementation of large-scale data science and full-stack products.

Responsibilities

• Lead data science implementations for business programs in production environments at scale.
• Design modular, maintainable, and extensible software systems using proven architecture principles and design patterns.
• Conduct and govern AI experimentation to determine solution optionality and business impact.
• Implement end-to-end ML Ops, including model monitoring, feedback loops, and automation.
• Build full-stack applications covering user story formulation, frontend, middleware, backend, and API integration.

Required Skills

• 5+ years of experience in software and machine learning environments.
• Proficiency in Python, PySpark, and Java.
• Strong knowledge of Machine Learning, Artificial Intelligence, statistics, and probability.
• Experience with frontend frameworks including Angular and React.
• Hands-on experience with cloud computation systems (AWS, Azure, or GCP) and their respective ML stacks.
• Practical knowledge of microservices, Docker, and Kubernetes.
• Experience with SQL and NoSQL databases, ETL, and CI/CD pipelining.
• Bachelor's degree in Computer Science.

Preferred Skills

• Experience with Gen AI, LLMs (OpenAI, Gemini), NLP, and computer vision.
• Cloud certifications such as AWS Solutions Architect, Google ML Professional, or Azure Solutions Architect Expert.
• Architecture certifications like TOGAF or Zachman.

Key Skills

Education

Bachelor's degree in Computer Science