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Staff Software Engineer leading the design and evolution of Stripe’s ML Platform, building scalable infrastructure for ML training, model serving, and AI workflows to power Stripe’s fintech products.
The Senior AI/ML Infrastructure Engineer builds and maintains the platform, tooling, and Kubernetes-based infrastructure required to train and deploy large-scale machine learning models. The role focuses on enabling ML engineers and researchers through scalable platform SDKs and GPU-optimized compute environments.
Company Overview Deepgram is the leading platform underpinning the emerging trillion-dollar Voice AI economy, providing real-time APIs for speech-to-text (STT), text-to-speech (TTS), and building production-grade voice…
Build ML infrastructure—training pipelines, model registries, and deployment systems—for XYZ Reality's Construction Intelligence platform, using Python, PyTorch, Docker, and Kubernetes to take AI models from research into production on wearable AR devices.
Overview Microsoft AI is looking for a Member of Technical Staff, Multimodal Infrastructure to help build the next wave of capabilities of our personalized AI assistant, Copilot. We’re looking for someone who will…
Builds and scales the ML compute platform for autonomous driving, focusing on Kubernetes-based orchestration, distributed training, and resource governance using tools like Argo Workflows and Ray.
Causal Labs is seeking a Machine Learning Infrastructure Engineer to build and maintain the distributed training and inference backbone for a Large Physics foundation Model. The role requires deep expertise in large-scale ML infrastructure, GPU optimization, and distributed training frameworks to support the company's mission of developing general causal intelligence.
The Engineering Manager will lead the Network Security team at Anthropic, overseeing the design and implementation of secure networking controls for cloud and bare-metal data centers. This role involves managing senior engineers, setting security strategy, and ensuring secure-by-default infrastructure to support large-scale AI research and production environments.
Why this role exists K0rdent AI is the orchestration layer that turns raw, disaggregated GPU infrastructure into a multi-tenant, production-ready AI cloud — without locking companies into a single hyperscaler or…
The Associate Director of Platform Engineering will lead the team managing hybrid compute infrastructure, developer platforms, and scientific compute environments for drug discovery. The role involves setting architectural strategy for Kubernetes-based clusters and MLOps pipelines while collaborating with data science and engineering teams.
The Software Golang Engineer will design and build a managed Slurm service on Kubernetes, focusing on scheduling and orchestration for GPU-intensive workloads. The role involves developing observability and remediation tools using Go and cloud-native technologies.
The Principal Applied AI/ML Scientist leads the design and implementation of enterprise-level AI/ML solutions, including generative AI and multimodal systems, to drive business value at lululemon. This role involves acting as a strategic advisor to senior leadership while mentoring technical teams and establishing standards for AI innovation and production.
The AI/ML ASIC Architect will design and define architecture specifications for next-generation AI storage and accelerator solutions, focusing on I/O subsystems and high-performance interfaces like PCIe, CXL, and UCIe. The role involves collaborating with cross-functional teams to optimize performance, power, and area for large-scale LLM training and inference workloads.
This role involves leading QA automation initiatives for data and analytics projects, focusing on building scalable test frameworks and implementing AI agents for autonomous testing. The position requires deep expertise in GenAI, LLM orchestration, and traditional QA automation tools like Selenium and Java.
Designs and optimizes large-scale pre-training strategies for AI language models, focusing on data engineering, distributed training, and long-context techniques to enhance model performance.
The Technical Architect will design and implement scalable, fault-tolerant AI systems on Google Cloud, bridging the gap between research and production. The role involves leading MLOps lifecycles, defining compute strategies for AI workloads, and mentoring teams to build resilient, cloud-native architectures.
Builds scalable ML infrastructure for AI-driven material discovery, integrating simulations, lab data, and scientific literature into a closed-loop autonomous system.
Senior Machine Learning Research Engineer About Relation Relation is a sector defining TechBio company developing transformational medicines, with technology at our core. Our ambition is to understand human biology in…
The Role Training robot foundation models is expensive and iteration speed is everything: the faster our robotics engineers can launch a job, get results, and try the next idea, the faster the whole company moves. We…
Designs and develops next-gen search and conversational discovery features for Apple’s media platforms (App Store, Music, TV, Podcasts, Books, Fitness+), leveraging generative AI, LLMs, and distributed ML systems to enhance user content discovery across iOS, macOS, and other Apple devices.
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