Top Tech Jobs & Startup Jobs

Lead architecture and low-level optimizations for high-performance AI inference. Benchmark and tune GPU kernels, memory and precision management, parallelize across multi-node GPU clusters, implement quantization (FP8/INT8/FP4), advise on hardware/software stacks (CUDA/ROCm/Triton/TensorRT), mentor engineers, and collaborate to turn hardware limits into shippable inference products.

Lead benchmarking and low-level performance optimization for GPU-based inference. Solve memory, precision, and parallelization bottlenecks, tune kernels (CUDA/Triton/ROCm/AMD AITER), implement quantization (FP8/INT8/FP4), advise on hardware/software integration, mentor engineers, and translate hardware limits into shippable features for high-throughput, low-latency inference fleets.

Lead design and implementation of high-scale, resilient AI inference data plane services. Architect distributed LLM serving systems, optimize performance (tensor/data parallelism, KV-cache routing), build on Kubernetes-native inference frameworks, contribute to open-source projects, mentor engineers, and operate production services with strong observability and SLOs.

Lead design and delivery of high-scale, resilient distributed inference data-plane services for LLM hosting. Optimize performance (tensor/data parallelism, KV-cache routing, prefill/decode disaggregation), collaborate cross-functionally, contribute upstream to open-source inference projects, mentor engineers, and operate production services with strong SLOs and observability.

Lead design and implementation of high-scale, multi-tenant AI inference data plane services. Optimize distributed LLM serving (prefill/decode disaggregation, KV-cache routing, autoscaling, flow control), contribute upstream to open-source inference projects, mentor engineers, and operate resilient, observable production services running on Kubernetes and specialized AI hardware.

Lead design and delivery of high-scale, resilient distributed inference data plane services. Architect and optimize inference hosting (tensor/data parallelism, KV-cache routing, prefill/decode disaggregation), contribute upstream open-source projects, mentor engineers, and maintain operational excellence and SLOs for a multi-tenant AI inference cloud.

Lead design, build, and operate high-scale, resilient inference data plane services for LLMs. Drive distributed system architecture, performance optimization (tensor/data parallelism, KV-cache routing), Kubernetes-native serving frameworks, open-source contributions, mentorship, and production SLO-driven operations to deliver Inference-as-a-Service with low latency and high availability.

Set technical direction for Security Products (IAM, KMS, CSPM, ISPM). Design cross-domain identity, key management, and posture architectures, drive standards and protocols adoption, represent security architecture to execs, and mentor engineers.

Lead design and implementation of secure global network infrastructure. Architect security standards, conduct threat modeling and network assessments, build security automation and tooling, integrate controls with SDN/BGP/MPLS platforms, support incident response, and mentor engineering teams to maintain resilient, observable network security posture.

Lead strategy and execution for DigitalOcean's Serverless Compute (App Platform, Functions, Observability). Define multi-year roadmap, drive scalability, reliability, and operational excellence, partner cross-functionally, and build a high-performance distributed engineering organization to improve developer experience and business growth.