Principal Machine Learning Engineer
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The role
Own the execution layer of AI systems, turning research into production-grade ML pipelines spanning data, training, evaluation, inference, and deployment.
Fine-tune and adapt transformer models using LoRA, QLoRA, SFT, DPO, and distillation.
Architect scalable inference systems that balance latency, cost, and reliability, with focus on GPU memory efficiency.
Design data systems for high-quality synthetic and real-world training data, and implement evaluation pipelines for performance, robustness, safety, and bias.
Lead production deployment, including GPU optimization, latency reduction, scaling policies, and robust monitoring.
Collaborate with backend, mobile, and desktop teams to integrate ML systems into products, operating under real production constraints.
Fine-tune and adapt transformer models using LoRA, QLoRA, SFT, DPO, and distillation.
Architect scalable inference systems that balance latency, cost, and reliability, with focus on GPU memory efficiency.
Design data systems for high-quality synthetic and real-world training data, and implement evaluation pipelines for performance, robustness, safety, and bias.
Lead production deployment, including GPU optimization, latency reduction, scaling policies, and robust monitoring.
Collaborate with backend, mobile, and desktop teams to integrate ML systems into products, operating under real production constraints.
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