Top Tech Jobs & Startup Jobs in NYC, NY

Own fleet-wide reliability and operations programs for a rapidly scaling AI cloud infrastructure platform. Establish reliability metrics, dashboards, OKRs, and success criteria; identify systemic gaps across compute, storage, networking, hardware, firmware, software, and operations; and lead cross-functional initiatives that improve fleet readiness, availability, utilization, and stability. Manage dependencies, risks, incident follow-ups, root cause actions, and executive communications while ensuring improvements scale with fleet growth.

Design, develop, and maintain network datapath monitoring and observability infrastructure for GPU cloud services. Build real-time network telemetry and analytics pipelines across host networking, smart NICs, and overlay/underlay networks. Collaborate with DevOps, production, and data platform teams; troubleshoot Kubernetes and cloud networking issues; participate in on-call support, code reviews, architecture decisions, and continuous infrastructure improvements.

Design and implement distributed, exabyte-scale storage systems for AI workloads, including S3-compatible object storage and dedicated storage clusters. Improve storage reliability, durability, security, observability, throughput, latency, and resilience using technologies such as RDMA, GPU Direct Storage, and distributed filesystems. Monitor and troubleshoot production systems, develop performance dashboards, analyze telemetry, collaborate across infrastructure teams, and mentor engineers.

Design, build, and operate secure sandboxed runtime environments for Kubernetes and GPU-accelerated workloads. Develop GPU-aware scheduling, isolation, and resource management strategies; optimize container, VM, I/O, and GPU performance; conduct profiling and benchmarking; and contribute to Linux, container runtime, virtualization, and GPU driver architecture. Collaborate with security, platform, and infrastructure teams to establish runtime isolation and performance standards for multi-tenant systems.

Own the roadmap and execution for W&B Models, an experiment-tracking platform for AI researchers. Improve experiment organization, training visualization, monitoring, evaluations, and large-scale analysis across web and mobile. Conduct user research, translate ML workflows into product decisions, collaborate with engineering and design, and use data and feedback to launch polished, high-performing experiences. The role requires deep familiarity with ML research, technical product management, data visualization, AI tools, and developer or researcher audiences.

Lead an engineering team responsible for CI, build systems, artifact management, and release automation. Set technical direction, modernize developer workflows, improve reliability and performance, track delivery metrics, manage technical debt, and drive adoption of platform capabilities. Mentor engineers through regular one-on-ones and career development while partnering with senior technical stakeholders. The role requires hands-on experience with scalable CI and build platforms, Kubernetes, cloud technologies, automation, and infrastructure as code.

Lead CoreWeave’s product regulatory governance program and advise Product, Engineering, AI, Security, Supply Chain, and Operations teams. Responsibilities include reviewing products and AI capabilities, assessing international regulatory risks, embedding privacy, responsible AI, security, and data-governance requirements, advising on market entry and launches, monitoring global laws, and leading regulatory inquiries, audits, investigations, and remediation.

Own CoreWeave’s AI training infrastructure narrative, positioning, competitive messaging, customer evidence strategy, go-to-market approach, and sales enablement. Translate Kubernetes, scheduling, bare-metal performance, and distributed training capabilities into compelling messaging for AI research leaders, platform engineers, developers, and technical architects. Partner with technical teams on benchmarking, collaborate with Sales, Solutions Architects, and DevRel, and measure impact through deal velocity, contract value, competitive win rates, adoption, and retention.

Serve as the named technical partner for financial services customers, driving adoption and expansion of CoreWeave's AI platform. Provide hands-on support for training, fine-tuning, evaluating, and deploying LLMs and other deep learning workloads; solve technical problems, create demos/PoCs, advise on production performance, reliability, governance, and infrastructure efficiency; collaborate with sales, field engineers, product, and engineering to ensure customer success.

Own and evolve a Kubernetes-native test framework that qualifies host images on real hardware. Build test harnesses, extend coverage into HPC, Slurm-on-Kubernetes and firmware/hardware, keep CI fast and reliable at fleet scale, and own results, reporting, and triage. Collaborate with kernel, firmware, imaging, and HPC teams and explore LLM-driven log triage and failure classification.