Description

Design and implement end-to-end AI/ML architectures, from data ingestion to model monitoring, while providing technical leadership to data science and platform teams.

This role is on-site.

Responsibilities

• Design comprehensive AI/ML architectures, including feature engineering, model deployment, and monitoring pipelines.
• Partner with business and technical stakeholders to translate use cases into scalable AI solutions aligned with enterprise goals.
• Establish best practices for AI adoption, including reusable patterns, accelerators, and governance frameworks.
• Collaborate with data architecture teams to ensure data quality, lineage, and governance for AI workloads.
• Mentor data scientists, ML engineers, and platform teams on technical execution and architectural decisions.

Required Skills

• 8+ years of experience in data, analytics, or platform architecture roles focused on AI/ML solutions at scale.
• Strong knowledge of machine learning, deep learning, and Generative AI concepts.
• Proficiency in Python and SQL.
• Experience with ML frameworks such as TensorFlow and PyTorch.
• Hands-on experience with cloud AI platforms (Azure, AWS, GCP).
• Proficiency with MLOps tools and data engineering platforms like DataStage or Spark.
• Proven expertise in deploying AI models into production environments.
• Ability to manage stakeholder expectations and communicate effectively with leadership.

Preferred Skills

• Experience establishing governance frameworks for AI adoption.
• Background in data lineage and quality assurance for enterprise AI workloads.

Key Skills

Education

Any Graduate