Description

You architect and build advanced AI agents and deep learning models that solve complex, real-world problems at scale.

This role is on-site.

Responsibilities

• Curate and maintain high-quality datasets to drive data coverage for critical industry use cases.
• Translate ambiguous, high-level requirements from cross-functional teams into actionable machine learning tasks.
• Define and drive MLOps best practices, including containerization, model versioning, and monitoring.
• Optimize complex ML models and agents for performance, scalability, and cost-efficiency.

Required Skills

• 7+ years of progressively responsible experience in ML/Deep Learning roles.
• Expert-level proficiency in Python and PyTorch; TensorFlow experience is welcome.
• Master's or Ph.D. in Computer Science, Math, Engineering, Statistics, or a related quantitative field.
• Proven track record as a Principal or Lead ML Engineer with shipped production-ready projects.
• Extensive experience with Linux and bash scripting in production environments.
• Expertise in data structures, advanced data modeling, and large-scale software architecture.
• Strong practical statistical sense for designing rigorous experiments and interpreting results.
• Experience with cloud ML platforms (AWS SageMaker, Azure ML, Google Cloud Vertex AI).

Preferred Skills

• Experience with foundation models and self-supervised learning methods.
• Ability to architect AI agents capable of complex reasoning and external tool use.

Key Skills

Education

Any Graduate