Top Tech Jobs & Startup Jobs

Lead post-silicon functional validation for AI SoCs: plan, develop and debug bare-metal tests on FPGA/emulator and first silicon, build Python automation and regression suites, analyse failures, collaborate across hardware, firmware and platform teams, and improve test infrastructure and methodologies.

Lead test strategy and validate low-level Linux kernels, device drivers and platform tools. Design, build, run and report component-to-system tests, debug across hardware, firmware and software stacks, improve test infrastructure and mentor engineers to ensure production-ready drivers and platform reliability.

The SoC Architect designs and integrates sub-systems for advanced silicon devices, collaborates across teams, and mentors engineers.

The Electrical Engineer will design hardware systems for AI applications, develop schematics, create PCBs, and collaborate on designs through production.

Lead design, deploy and operate OpenStack-based private and public cloud services for high-performance AI systems. Mentor engineers, implement IAC and CI/CD, automate observability, benchmark and integrate hardware and 3rd-party networking/storage into production cloud deployments.

Lead strategic sourcing for memory and storage technologies, manage supplier relationships, negotiate commercial agreements, develop cost models and risk mitigation plans, support NPI and production ramps, and collaborate cross-functionally to secure capacity and optimise cost, quality, and supply resilience for AI infrastructure platforms.

Lead global sourcing strategy for contract manufacturing partners: build and mentor a sourcing team, negotiate long-term agreements, develop cost models, ensure capacity and supply continuity, drive cross-functional alignment and supplier performance.

Lead architecture and development of manufacturing test solutions and test-executive software for host processor modules, server blades, and rack-scale systems. Define test coverage, create automated test content, drive cross-functional debug and root-cause analysis, and improve manufacturing quality and testability across hardware, firmware, and software teams.

Design and implement features, optimize software performance, manage code quality, conduct code reviews, and mentor team members in developing machine learning frameworks like Triton.

Design and optimize AI data center networks, focusing on high-performance computing and network fabrics, while collaborating with cross-functional teams.