Principal Engineer, AI Model LifeCycle
The Principal Software Engineer for the Model LifeCycle team is responsible for managing fine-tuning systems for large foundation models, including multi-node orchestration, checkpointing, failure recovery, and cost-efficient scaling. They implement and maintain end-to-end training pipelines for Large Language Models, distillation and reinforcement learning pipelines, and agent execution infrastructure. Additionally, they manage dataset, model, and experiment management including versioning, lineage, evaluation, and reproducible fine-tuning at scale. The role involves close collaboration with product, business, and platform teams to shape core abstractions and APIs, influence long-term architectural decisions around training runtimes, scheduling, storage, and model lifecycle management, and contribute to the open-source LLM ecosystem. This role offers significant ownership in designing and building core systems from first principles.
Tech Lead, Android Core Product - Córdoba, Argentina
Work alongside machine learning researchers, engineers, and product managers to bring AI Voices to customers for various use cases. Deploy and operate the core ML inference workloads for the AI Voices serving pipeline. Introduce new techniques, tools, and architecture to improve the performance, latency, throughput, and efficiency of deployed models. Build tools to identify bottlenecks and sources of instability, and design and implement solutions to address the highest priority issues.
Tech Lead, Android Core Product - Buenos Aires, Argentina
Work alongside machine learning researchers, engineers, and product managers to bring AI Voices to customers for a diverse range of use cases; deploy and operate the core ML inference workloads for the AI Voices serving pipeline; introduce new techniques, tools, and architecture to improve the performance, latency, throughput, and efficiency of deployed models; build tools to identify bottlenecks and sources of instability and design and implement solutions to address the highest priority issues.
Tech Lead, Android Core Product - Medellín, Colombia
Work alongside machine learning researchers, engineers, and product managers to bring AI Voices to their customers for a diverse range of use cases. Deploy and operate the core ML inference workloads for AI Voices serving pipeline. Introduce new techniques, tools, and architecture that improve the performance, latency, throughput, and efficiency of deployed models. Build tools to provide visibility into bottlenecks and sources of instability and design and implement solutions to address the highest priority issues.
Tech Lead, Android Core Product - Lagos, Nigeria
Work alongside machine learning researchers, engineers, and product managers to bring AI Voices to customers for diverse use cases. Deploy and operate the core machine learning inference workloads for the AI Voices serving pipeline. Introduce new techniques, tools, and architecture to improve the performance, latency, throughput, and efficiency of deployed models. Build tools to provide visibility into bottlenecks and sources of instability and design and implement solutions to address the highest priority issues.
Tech Lead, Android Core Product - Kolkata, India
Work alongside machine learning researchers, engineers, and product managers to bring AI Voices to customers for various use cases. Deploy and operate the core ML inference workloads for the AI Voices serving pipeline. Introduce new techniques, tools, and architecture to improve performance, latency, throughput, and efficiency of deployed models. Build tools to identify bottlenecks and sources of instability and design and implement solutions to address high priority issues.
Tech Lead, Android Core Product - Noida, India
Work alongside machine learning researchers, engineers, and product managers to bring AI Voices to customers for diverse use cases; deploy and operate the core ML inference workloads for AI Voices serving pipeline; introduce new techniques, tools, and architecture that improve performance, latency, throughput, and efficiency of deployed models; build tools to identify bottlenecks and sources of instability and design and implement solutions to address the highest priority issues.
Tech Lead, Android Core Product - Luxembourg City, Luxembourg
Work alongside machine learning researchers, engineers, and product managers to bring AI Voices to customers for a diverse range of use cases. Deploy and operate the core ML inference workloads for the AI Voices serving pipeline. Introduce new techniques, tools, and architecture to improve performance, latency, throughput, and efficiency of deployed models. Build tools to identify bottlenecks and sources of instability and design and implement solutions to address the highest priority issues.
Tech Lead, Android Core Product - Coimbra, Portugal
Work alongside machine learning researchers, engineers, and product managers to bring AI Voices to customers for a diverse range of use cases. Deploy and operate the core ML inference workloads for the AI Voices serving pipeline. Introduce new techniques, tools, and architecture that improve the performance, latency, throughput, and efficiency of deployed models. Build tools to identify bottlenecks and sources of instability and design and implement solutions to address the highest priority issues.
Tech Lead, Android Core Product - Cardiff, United Kingdom
Work alongside machine learning researchers, engineers, and product managers to bring AI Voices to customers for a diverse range of use cases. Deploy and operate the core ML inference workloads for the AI Voices serving pipeline. Introduce new techniques, tools, and architecture that improve the performance, latency, throughput, and efficiency of deployed models. Build tools to gain visibility into bottlenecks and sources of instability and design and implement solutions to address the highest priority issues.
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