Jobs at d-Matrix

Build and lead d-Matrix’s investor relations function as the company prepares for public markets. Own the equity story, investor communications, shareholder and analyst relationships, capital-raise support, financial messaging, disclosure policies, IPO readiness, and IR infrastructure. Translate complex AI semiconductor technology and business milestones into clear investor materials while partnering with executive leadership, Finance, Legal, Communications, and external advisors. Hire and manage IR personnel and vendors and support investor meetings, conferences, and roadshows.

Lead global talent acquisition across multiple international markets, defining recruiting strategy, employer brand, executive and technical hiring, assessment standards, recruiting analytics, agency partnerships, onboarding, and internships. Manage recruiters and sourcers, advise senior leaders, close high-impact candidates, and use technology and AI to scale recruiting operations.

Own end-to-end performance of LLM inference workloads across orchestration, networking, serving frameworks, runtimes, operating systems, and accelerators. Diagnose regressions through profiling, improve latency, throughput, and stability, encode workload requirements into orchestration, develop telemetry and benchmarks, create investigation playbooks, and mentor engineers. Work spans Kubernetes, heterogeneous hardware, speculative decoding, KV-cache management, batching, NUMA, and cross-team root-cause resolution.

Set technical direction for AI-enabled automation across build, CI, testing, and release. Build agent harnesses and integrations with GitLab, Jira, test results, logs, and observability systems. Develop evaluation methods, guardrails, and auditability for nondeterministic automation. Deliver quality engineering capabilities such as failure attribution, defect deduplication, coverage-gap analysis, and release-readiness summaries while mentoring engineers and guiding cross-team adoption.

Own end-to-end testing and release engineering for an inference cloud platform. Build automated tests and infrastructure for Kubernetes deployments across GPU, Corsair, on-premises, and Azure environments. Define release strategies, versioning, promotion, rollback, compatibility testing, and release gates covering functionality, accuracy, upgrades, and performance. Partner across engineering teams to improve test quality, enable feature-owned testing, and scale reliable releases for distributed AI serving systems.

Owns production infrastructure across Kubernetes, CI/CD, Linux systems, virtual machines, and AI accelerator environments. Responsibilities include incident response, troubleshooting, automation, monitoring, alerting, patching, upgrades, certificate renewals, capacity checks, runbook development, and on-call support. The engineer collaborates across IT and product software teams and contributes to infrastructure design and build work.

Lead an eight-person Software Quality Engineering team responsible for quality strategy, automation, test frameworks, functional and end-to-end testing across firmware, compilers, runtimes, and inference serving. Establish numerical accuracy and performance regression detection, release gates, defect triage, quality metrics, and resource-efficient test tiering. Hire and develop engineers while partnering closely with development teams to improve testing standards, CI integration, and engineering confidence.

Lead d-Matrix’s Bazel migration and build infrastructure. Own the build graph, hermetic toolchains, caching, remote execution, test migration, reproducible builds, and CI/CD improvements across MLIR, Rust, C++, and Python codebases. Establish build-time metrics, improve cache reliability and performance, operate production executor infrastructure, and promote Bazel best practices across engineering teams.

Own strategic sales for d-Matrix’s AI inference hardware and software platform, managing complex enterprise sales cycles from technical evaluation through multi-rack deployment. Grow hyperscaler, neocloud, AI lab, and enterprise accounts; negotiate pricing and commercial terms; manage forecasting and pipeline reviews; coordinate solutions engineering, operations, supply chain, and ecosystem partners; and build scalable sales processes and playbooks.

Drive revenue growth for d-Matrix’s AI inference platform by managing strategic hyperscaler, neocloud, AI lab, and enterprise accounts. Lead complex technical sales cycles from proof-of-concept through production deployment, negotiate multimillion-dollar hardware and platform deals, manage forecasting and pipelines, coordinate with product, engineering, operations, supply chain, and partners, and build scalable sales processes and playbooks.

Provide IT support for APAC users and offices, administering Microsoft 365, supporting macOS and Windows devices, troubleshooting hardware, wireless networks, cybersecurity issues, and office equipment. Manage onboarding, laptop procurement and deployment, documentation, software upgrades, migrations, and IT projects. The role requires strong troubleshooting, communication, organization, and independent prioritization skills. Preferred experience includes JAMF Pro, Intune, managed wireless networks, Jira, and Confluence.

Build production-grade automation for diagnosing and resolving CI/CD failures, identifying regressions and problematic merges, and improving developer time-to-signal. Design scalable compute and storage across cloud and on-premises environments, lead release engineering practices, integrate AI with deterministic automation, and promote tooling and engineering best practices across development and quality teams.

Own reliability, automation, and observability across colocation facilities, on-premises GPU clusters, cloud environments, and customer-facing platforms. Provision and troubleshoot servers, networking, storage, Kubernetes, and hardware; build infrastructure-as-code and automation; manage capacity and cloud spend; create monitoring and alerting; support incident response, on-call operations, and root-cause analysis. Partner with hardware and software teams on CI/CD, QA, HPC workloads, and customer deployments.

Responsible for demand and supply planning for server systems, managing partner contracts, and ensuring inventory and customer order fulfillment through cross-functional collaboration.

Build and lead the Site Reliability Engineering function across cloud, colocation, on-premises labs, and customer-facing services. Establish SLOs, observability, incident management, IaC automation, self-healing infrastructure, FinOps, capacity planning, and shared-storage architecture. Lead SRE and data center teams, hire and develop engineers, manage reliability and technical direction, and serve as the senior incident escalation point.

Leads rack-scale mechanical design for AI inference hardware, covering chassis, sheet metal enclosures, cooling architectures, and high-power connections. Owns systems from concept through validation, NPI, and mass production. Responsibilities include reliability testing, CAD and FEA, tolerance analysis, supplier and ODM management, production debugging, root-cause analysis, liquid-cooled rack integration, and mentoring engineers. Requires strong OCP, data center hardware, manufacturability, and mechanical leadership experience.

Own compensation analytics, market benchmarking, salary structures, job leveling, internal equity, merit and bonus modeling, and HR reporting. Manage core People Operations processes including onboarding, offboarding, records, payroll coordination, benefits, and HR systems administration. Partner with HR, business, recruiting, mobility, legal, and employee relations teams to support data-driven HR services and maintain compliant policies and procedures.

Leads full-cycle PCB layout for complex AI accelerator cards and system baseboards. Owns high-speed routing, constraint management, stack-up definition, power delivery layouts, and design methodology. Develops SKILL, Python, or TCL automation for layout audits and reporting, and partners with power, ASIC, fabrication, and manufacturing teams to ensure DFM, DFT, DFA, and high-yield production. Requires expertise in high-density, high-speed PCB design, including 112G/224G SerDes, DDR5/HBM, HDI, and advanced materials.

Analyze emerging AI workloads and build analytical performance models and architecture simulators for current and future AI inference accelerator hardware. Collaborate with hardware, compiler, inference server, kernel, and product teams to validate assumptions, identify HW/SW optimization opportunities, incorporate architecture research, and document methodologies. The role is a hands-on technical contributor focused on performance analysis across the hardware/software boundary.

Design analog-mixed signal integrated circuits, optimize for low power performance, and collaborate on silicon bring up and debugging.