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Develops and optimizes AI model-serving systems on GPU infrastructure, focusing on latency, reliability, and cost while working with tools like Triton, vLLM, and Kubernetes.
Leads architecture and performance for CoreWeave’s Kubernetes-native AI inference platform, optimizing low-latency, high-throughput systems and GPU resource management.
Design and deploy secure AI workloads for U.S. government agencies, ensuring compliance with FedRAMP and DoD standards while optimizing GPU-powered cloud infrastructure for mission-critical applications.
Write, profile, and optimize CUDA kernels for LLM inference to maximize throughput and minimize latency on NVIDIA GPUs, using DSLs like Triton or Mojo and benchmarking with MLPerf.
CoreWeave is The Essential Cloud for AI™. Built for pioneers by pioneers, CoreWeave delivers a platform of technology, tools, and teams that enables innovators to build and scale AI with confidence. Trusted by leading…
Design and deliver AI infrastructure demos and proofs-of-concept for new customers, partnering with sales and engineering to onboard greenfield AI teams onto CoreWeave’s GPU-powered cloud platform.
Build and optimize AI infrastructure performance monitoring tools, ensuring high availability and observability for CoreWeave’s cloud platform.
Senior Account Solutions Architect at CoreWeave serves as the named technical partner to existing customers, helping AI teams deepen platform adoption, unblock technical issues, and scale LLM workloads in production across the full stack. Core skills: Python, hands-on LLM/deep learning deployment, and major cloud platforms.
Staff Product Manager at CoreWeave owning the strategy, roadmap, and go-to-market for AI inference services on its GPU cloud platform — defining the inference product portfolio, engaging customers, and leading cross-functional teams. Requires deep knowledge of foundation-model inference, inference engines, and cloud-native infrastructure.
Source: Paraform - Compensation: $176,000-$224,000 base; OTE $220,000-$280,000 (80/20 base/variable, variable paid quarterly). Candidates with 10+ years may be considered above range. Meaningful equity on top of OTE.…
A cybersecurity-focused data engineer who builds ingestion pipelines and normalizes heterogeneous security event data for a cognitive SIEM platform supporting SOC operations. Day to day spans Python/SQL ETL across SIEMs, network sensors and CTI feeds, data modeling/enrichment with MITRE ATT&CK context, and preparing datasets for AI/RAG features.
ClusterVision’s mission is to lead the market in full-service HPC/AI, Storage, Machine Learning and Cloud enablement. As the enabler of our customers’ complex IT requirements, our customers' success is our success.…
Engineer on DoorDash's GenAI Platform team building production ML infrastructure: real-time GPU serving and high-throughput batch inference for open-weight LLMs/VLMs, plus fine-tuning (SFT/DPO/LoRA), LLM Gateway, evals, guardrails and cost attribution. Core stack: Python, distributed systems, GPU inference engines, Kubernetes, AWS/GCP.
Responsibilities: Designing and deploying scalable, multi-tenant cloud (AWS or Azure) and hybrid/on-premises architectures tailored to diverse client needs, including specialized infrastructure for AI and machine…
We're building a team of engineers working at the frontier of AI-assisted software development. Whatever your backend stack — Node.js, TypeScript, Python, PHP, .NET / C# or Java — if you already build real products…
About the role We are building a real-time conversational AI voice platform. An orchestrator runs every call through Voice Activity Detection, Speech-to-Text, LLM-based agent matching, tool calling against ServiceNow…
Pieoneers is seeking a Senior AI Engineer to join our AI development team in Vancouver, BC with opportunities to work remotely. You'll help clients turn AI ideas and prototypes into reliable production products…
#junior #middle #100k #удаленка от 80 000 до 120 000 ₽ за месяц, на руки Опыт работы: 1–3 года Полная занятость График: 5/2 Формат работы: удалённо ☑️ Чем предстоит заниматься -Разрабатывать и поддерживать…
Owns the target architecture and platform for an enterprise AI platform — Kubernetes across Azure, on-prem, and air-gapped sites — covering IaC, GitOps delivery (Helm, Argo CD/Flux), GPU model serving, sandboxed browser fleets, observability, security, and cost, while leading platform engineering and mentoring a junior DevOps engineer.
DaphOS is hiring a (Senior) Data Scientist to build AI features for its B2B healthcare platform that helps hospitals plan processes and staffing. The role blends classical ML, probabilistic modeling and optimization with LLM work (RAG, information extraction, agentic workflows), including evaluations and Python-based integration into the product backend.
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