Technical Lead, Machine Learning
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El puesto
Own and build end-to-end ML pipelines spanning data, training, evaluation, inference, and deployment.
Fine-tune and adapt models using LoRA, QLoRA, SFT, DPO, and distillation to maximize performance.
Architect scalable inference systems balancing latency, cost, and reliability in production.
Design data systems for high-quality synthetic and real-world training data and robust evaluation.
Own production deployment with GPU optimization, memory efficiency, latency reduction, and scalable policies.
Collaborate with application teams to integrate ML into backend, mobile, and desktop products, shipping rapidly under real constraints.
Fine-tune and adapt models using LoRA, QLoRA, SFT, DPO, and distillation to maximize performance.
Architect scalable inference systems balancing latency, cost, and reliability in production.
Design data systems for high-quality synthetic and real-world training data and robust evaluation.
Own production deployment with GPU optimization, memory efficiency, latency reduction, and scalable policies.
Collaborate with application teams to integrate ML into backend, mobile, and desktop products, shipping rapidly under real constraints.
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