Top Tech Jobs & Startup Jobs in San Francisco Bay Area, CA

Provide legal support for infrastructure procurement and enterprise commercial deals. Lead negotiations for GPU/cloud capacity, data center, networking, and vendor agreements; align vendor terms with customer contracts; manage export controls and data/privacy compliance; build templates, playbooks, and scalable procurement and sales workflows; support partnerships, reseller and go-to-market deals; and run procurement processes and vendor template libraries.

This role involves optimizing model serving layers for voice AI applications, working with inference engines, and improving performance for STT and TTS systems.

The Staff Machine Learning Engineer will optimize the inference layer for voice applications, focusing on model serving and real-time audio processing. Responsibilities include driving performance architecture, collaborating with model partners, and developing evaluation frameworks for STT and TTS models.

Provide hands-on IT support for in-office and remote employees across identity, devices, SaaS, and procurement. Administer Okta and MDM (macOS/Linux), manage asset lifecycle, create documentation and automations, support onboarding/offboarding, basic network/A/V troubleshooting, and contribute to security hygiene and IT projects.

Design and implement a scalable observability platform (metrics, logs, traces) using Prometheus, Grafana, ClickHouse/ClickStack, and OpenTelemetry. Build telemetry pipelines, automated monitoring, SLIs/SLOs, alerting, anomaly detection, and runbooks. Develop IaC and custom tools with Go, Python, Terraform, Ansible, and Helm. Collaborate on distributed tracing, lead incident response, and define observability best practices.

Design, deploy, and maintain large-scale hybrid data center networks; troubleshoot and analyze network issues; develop automation and tooling; evaluate and recommend hardware/software; manage vendor relationships; ensure reliability, scalability, and compliance; lead complex network projects and contribute to architecture and roadmaps.

Research intern contributing to agentic AI: develop and implement novel training methods, design experiments and datasets, evaluate agent behavior and safety, document findings, and communicate results to the team.

The Manager will analyze and benchmark compute infrastructure sourcing and operations, driving strategic decisions and optimizing resource allocation across sites and vendors.

Work on developing and optimizing GPU-accelerated kernels and algorithms for ML/AI. Collaborate with modeling, hardware, and software teams to co-design GPU kernels and architectures, integrate GPU solutions, and profile and optimize performance using GPU profiling tools.

Develop and maintain a platform for customizing open-source models, integrating Model Shaping with Inference, adding inference engine features and RL optimizations, ensuring production stability and 24/7 availability, and collaborating with product, research, and engineering teams to support fine-tuning, RL, and evaluation workflows.