Description

You lead the identification, training, and refinement of advanced deep learning models to solve complex, real-world problems at scale.

Responsibilities

• Curate and maintain effective datasets, driving data coverage and quality for critical industry use cases.
• Translate ambiguous, high-level needs from cross-functional teams into actionable ML tasks.
• Drive and define MLOps best practices, including containerization, model versioning, and monitoring.
• Architect and build advanced AI agents capable of complex reasoning and external tool use.
• Optimize complex ML models and agents for performance, scalability, and cost-efficiency.

Required Skills

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

Key Skills

Education

Any Graduate