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Build and maintain the backend and API platform powering SGLang and Miles, including REST/gRPC services, authentication, multi-tenancy, and monitoring for AI infrastructure.
Director-Level AI Scientist – Foundation Models & Generative AI Principal AI Scientist United States (Remote) Director-Level AI Scientist – Foundation Models & Generative AI Remote (U.S.) | Full-Time | $300,000…
A Staff/Principal ML Training Systems Engineer owns large-scale multimodal training performance end-to-end at a robotics foundation-model company — diagnosing compute/communication/memory bottlenecks, designing parallelism and distributed-training strategies across thousands of GPUs, building performance measurement tooling, and partnering closely with researchers. Core stack: PyTorch (JAX a plus)
Senior ML Engineer building novel geospatial analytics, change detection, and computer vision models for Defense and Intelligence applications using Python, PyTorch/TF, and cloud infrastructure (AWS/GCP) at a satellite imagery company.
An applied ML lead role at JPMorgan Chase's Corporate Sector AI/ML & Data Platform team: you own ML and generative-AI solutions end to end, from problem framing and experimentation through production, using Python, PyTorch/TensorFlow, and LLM techniques (RAG, agents, fine-tuning), while mentoring others and raising engineering standards.
Senior applied ML role on JPMorgan Chase's Applied AI & ML Data Platforms team in Manhattan: design, build, and productionize generative AI/LLM solutions (agents, RAG, fine-tuning) with hands-on Python, partnering with product and engineering to turn business needs into reliable models and platform capabilities.
Design and optimize end-to-end AI accelerator software, from low-level kernels to distributed training and inference, driving hardware-software co-design for Microsoft’s cloud-scale AI systems.
Overview Microsoft Research is working to transform the future of artificial intelligence by bridging the gap between cutting-edge general AI and the specialized, real-world applications that drive meaningful impact.…
Senior backend engineer designing and scaling systems for an AI development platform — distributed training infrastructure, workloads, and platform APIs. Hybrid role based in the London hub, collaborating with teams across New York and San Francisco.
Founding ML software engineer on Wayve's MEGA team, building foundation models for general-purpose robots and autonomous driving. Day to day: design and maintain scalable ML pipelines, distributed training and data infrastructure, and shared tooling that lets researchers train and evaluate large multimodal models reliably.
About the Team: The Inference Infrastructure team is the creator and open-source maintainer of AIBrix, a Kubernetes-native control plane for large-scale LLM inference. We are part of ByteDance’s Core Compute…
About us Re-architecting Engineering for the Age of Intelligence PhysicsX is the physics AI company for industrials. The company’s mission is to accelerate hardware innovation by overhauling what industrial engineering…
Employment Type: Full-Time Work Setting: In-office/Remote Work Location: United States, New York, Mexico, San Francisco, Canada Work Hours: Office hours Find out more here: https://semianalysis.com About SemiAnalysis…
Embedding Cluster Engineer: Cloud Infrastructure Specialist Summary We are seeking an experienced Cluster Infrastructure Engineer to design, implement, and maintain our vector embedding infrastructure on cloud…
Founded in 2016 in Silicon Valley, Pony.ai has quickly become a global leader in autonomous mobility and is a pioneer in extending autonomous mobility technologies and services at a rapidly expanding footprint of sites…
Job Description Changing the world through digital experiences is what Adobe’s all about. We give everyone—from emerging artists to global brands—everything they need to build and deliver outstanding digital…
Principal-level ML architect at Adobe responsible for end-to-end technical coherence across large-scale distributed training systems, inference infrastructure, model architecture, and data pipelines for next-generation video and image foundation models (GenRender6/Gen6.5, GenEdit1).
Senior Machine Learning Engineer on the Applied Science Data Frameworks team building foundational infrastructure for large-scale multimodal AI training and inference, working with distributed systems, data engineering fundamentals, and ML infrastructure using technologies like PyTorch, Apache Ray, Spark, and Docker.
The Opportunity Firefly is the new family of creative generative AI models coming to Adobe products that offers a new way to conceptualize, build, and scale content. It’s a natural extension of the technology Adobe has…
Your Role Sr. Machine Learning Engineer ROLES AND RESPONSIBILITIES Design, develop, train, fine-tune, and validate Machine Learning and Deep Learning models for ADAS/Automotive validation use cases. Build end-to-end ML…
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