Top Tech Jobs & Startup Jobs

Develop and maintain automated functional, integration, and end-to-end tests across software and hardware configurations. Create test plans, execute qualification runs, investigate failures, assess numerical accuracy and performance, report defects, verify fixes, and improve testing workflows. The role uses Python, Linux, CI pipelines, AI-assisted engineering, and potentially C++, ML inference, containers, hardware-in-the-loop testing, and distributed systems.

Leads quality and reliability engineering for AI hardware platforms spanning ASICs, cards, servers, racks, and clusters. Owns QMS, product and supplier quality, manufacturing quality, customer quality, component engineering, reliability programs, audits, RMA and failure analysis. Establishes quality metrics, drives shipment readiness, supports customer escalations, and builds a multidisciplinary quality organization for high-volume production.

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.