Ladders
United States
New
Machine Learning Engineer (Enterprise Technology)
- AI
- Machine Learning
- Python
- Pytorch
AI Summary
Key Highlights
Hands-on ownership of large-scale model architecture and distributed computing.
GPU performance optimization and production ML systems.
Principal-level technical influence and engineering standards.
Key Responsibilities
Define and evolve production ML architecture across the entire lifecycle.
Engineer scalable distributed training and inference environments using GPU infrastructure.
Lead GPU and serving optimization efforts for memory, latency, throughput, and cost.
Build dependable ML platforms with standards for maintainability, observability, and reliability.
Own ambiguous ML initiatives and make architectural tradeoffs for model quality, performance, and safety.
Partner with research and engineering teams to translate model capabilities into production experiences.
Develop robust data and evaluation workflows for model quality measurement and continuous improvement.
Set technical direction, resolve architecture challenges, and establish scalable engineering practices.
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Technical Skills Required
Benefits & Perks
Competitive cash and equity compensation
Health, dental, life insurance
401(k) benefits
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Nice to Have
Experience with high-performance LLM serving frameworks
GPU kernels or compilers expertise
Reinforcement learning workflows or multimodal models
Job Description
Our client is building advanced AI systems designed to move sophisticated machine learning capabilities from experimentation into dependable, real-world production. They are seeking an ML Architect to take hands-on technical ownership of large-scale model architecture, distributed computing, GPU performance, and the systems required to operate modern AI reliably at scale.
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