Top Tech Jobs & Startup Jobs

As a Customer Support Engineer, you will resolve technical challenges related to GPU clusters, collaborate with teams, and document processes to enhance customer satisfaction.

The role involves managing AI infrastructure programs, leading cross-functional teams, and driving product development for AI applications, ensuring project success and enhancing customer satisfaction.

The Customer Support Engineer provides technical support for AI solutions, engaging with customers to resolve issues, collaborating with teams, and contributing to product improvements.

Design and implement manifest-driven provisioning and reconciliation systems for GPU hosts and clusters. Build durable workflow engines, declarative self-service APIs, event-driven automation, self-healing pipelines, and production-grade control planes. Own coding, testing, CI/CD, and operate the platform in production to eliminate manual provisioning.

Own full sales cycle for strategic AI-native and enterprise accounts: generate pipeline, close new business, expand customers, and partner with Solutions, Engineering, and Research to run POCs and scale deployments. Provide technical and business insights to inform product and sales strategy.

As a Senior Developer Productivity Engineer, you will enhance CI/CD processes, optimize workflows, and build tools for efficient software delivery.

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.

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.