Lead Software Engineer - Machine Learning

📋 Description

• Bridge Research and Production: Translate data science research into production-ready
• Scale to Millions: Build ML APIs and data pipelines handling millions of requests with low latency.
• Architect from Scratch: Lead high-performance ML solutions and cross-functional adoption.
• End-to-End Pipeline Architecture: Design and manage ML pipelines from data prep to deployment and

🎯 Requirements

• Production ML Engineering: Translate complex models into optimized production software.
• MLOps Mastery: Lifecycle management for models from experiments to live production.
• Distributed Pipeline & API Design: Build scalable data pipelines and low-latency API
• System Telemetry & Monitoring: Establish monitoring for engineering efficiency, system health
• Technical Project Leadership: Prototyping, evaluate stacks, and align cross-functional teams.

🎁 Benefits

• Hybrid work options
• Competitive compensation and benefits