Description

You design and deploy end-to-end machine learning pipelines from data ingestion to production.

This role is on-site.

Responsibilities

• Build and deploy end-to-end ML pipelines covering data, modeling, and production stages.
• Develop scalable solutions for NLP, predictive modeling, and analytics.
• Productionize models using MLOps frameworks, CI/CD, monitoring, and governance.
• Create APIs and microservices for real-time model inference.
• Translate business, risk, and technology requirements into AI solutions.

Required Skills

• 15+ years of experience in relevant engineering roles.
• Strong Python programming and ML frameworks such as PyTorch.
• Experience with Spark and large-scale data processing.
• Hands-on experience deploying ML models to production environments.
• Proficiency with MLOps tools including MLflow, Docker, and Kubernetes.
• Experience managing CI/CD pipelines.
• Exposure to AWS cloud platforms.
• Experience with NLP and Generative AI (LLMs).

Preferred Skills

• Background in Financial Services or Capital Markets.
• Deep understanding of scalable architecture and data pipelines.

Key Skills

Education

Any Gradute