Description

Define and implement enterprise AI/ML solution architectures aligned with business goals and digital transformation initiatives.

This role is on-site.

Responsibilities

• Lead end-to-end AI solution delivery, including data ingestion, model development, validation, deployment, monitoring, and optimization.
• Design scalable AI/ML pipelines on AWS, Azure, and GCP, ensuring performance, reliability, and security.
• Establish MLOps best practices, including CI/CD pipelines, model lifecycle management, version control, and retraining strategies.
• Collaborate with stakeholders and engineers to translate business requirements into AI-driven solutions.
• Evaluate emerging AI technologies, mitigate risks related to model bias and drift, and provide technical mentorship.

Required Skills

• 10+ years of experience in software, data, or AI/ML solution architecture.
• Proven experience delivering enterprise-scale AI initiatives.
• Strong expertise in Machine Learning, Deep Learning, NLP, and Generative AI.
• Hands-on experience with TensorFlow, PyTorch, and Scikit-learn.
• Proficiency in Python, R, or Java.
• Experience deploying end-to-end AI solutions on AWS, Azure, or Google Cloud.
• Strong knowledge of MLOps, data engineering, and enterprise system integration.

Preferred Skills

• Bachelor’s or master’s degree in Computer Science, AI, Data Science, Machine Learning, Engineering, or IT.

Key Skills

Education

Any Graduate