Staff Machine Learning Engineer at well-funded consumer AI startup

You will lead the design and implementation of end-to-end machine learning systems for a next-generation consumer productivity platform. This includes building LLM fine-tuning pipelines, evaluation frameworks, and high-performance inference systems. Your work will directly shape the technical foundation of an AI-native application designed to automate complex daily workflows for millions of users globally.

Well-funded consumer AI startup

• Design and scale LLM training, fine-tuning, and evaluation pipelines for production-grade reliability.
• Optimize GPU-based inference systems for maximum throughput, low latency, and efficient resource utilization.
• Architect robust data processing pipelines to validate and manage high-quality training and evaluation datasets.

• Deep expertise in Python and hands-on experience with frameworks like PyTorch or JAX for large-scale models.
• Proven track record of deploying and monitoring production ML systems, specifically LLM-based applications.
• Strong background in distributed computing and optimizing inference engines like vLLM or TensorRT-LLM.

• Build a ground-up ML architecture for a high-scale consumer application used daily by millions.
• Backed by a profitable, large-scale parent organization, providing rare long-term stability and significant resources.
• High-impact leadership role shaping the core technical strategy of an ambitious, proactive AI-native ecosystem.