d-Matrix

DevOps Engineer

• Own reliability and availability of assigned infrastructure domains: colo server fleets, on-premises lab clusters, cloud environments (AWS, Azure, GCP), and customer-facing platform services.
• Perform hands-on infrastructure work: server provisioning, OS configuration, network setup, storage management, hardware troubleshooting from bare metal up.
• Support and operate high-speed interconnect environments — InfiniBand, RoCE, or high-speed Ethernet — in lab and colo settings.
• Conduct capacity planning and hardware lifecycle management for assigned infrastructure domains.
• Own IaC and configuration management (Terraform, Ansible) for your infrastructure domains — all provisioning and changes through code, not manual steps.
• Build automation to eliminate toil: host lifecycle management, fleet health checks, auto-remediation workflows, self-service tooling for engineering teams.
• Develop networking automations for cluster interconnects, VLAN management, lab network configurations.
• Design and maintain monitoring dashboards, alerting, and SLIs (Prometheus/Grafana, DataDog) for your infrastructure domains—ensuring signal quality and actionable alerts.
• Participate in on-call rotation; triage and resolve incidents from bare metal to application layer, distinguishing infrastructure faults from software or hardware product issues.
• Produce high-quality RCA reports for P0/P1 incidents with root cause analysis and tracked action items.
• Support and operate platform services used by external customers for hardware and software deployment collaboration with d-Matrix.
• Document platform configurations, access procedures, and operational runbooks for customer environments.
• Maintain high-quality runbooks, architecture diagrams, and troubleshooting guides—documentation is part of the job, not an afterthought.

Contract Site Reliability Engineer – AI Accelerator Infrastructure

• Own the SRE function end-to-end: define the team’s charter, establish SRE as a discipline within d-Matrix’s engineering culture, and drive buy-in across hardware, software, and executive stakeholders who have operated without a dedicated SRE team.
• Hire, develop, and retain a team of 3–5 SRE engineers; establish a culture of operational excellence, ownership, and continuous improvement from day one.
• Define the SRE technical roadmap: reliability architecture, automation priorities, capacity planning, and on-call model—and execute against it with your hands on the keyboard where needed.
• Serve as the senior technical escalation for critical incidents—guiding cross-team triage, driving RCA, and ensuring systemic fixes rather than point patches.
• Translate operational signals and infrastructure health into clear, actionable narratives for engineering leadership and executive stakeholders.
• Partner with the director of DevOps engineering to align infrastructure reliability with pipeline and automation delivery; the two functions must operate as a unified platform.
• Direct a dedicated data center & lab technician team—your hands and feet across on-premises and colocation facilities; set their work priorities, establish operational standards, and ensure physical infrastructure execution aligns with the SRE technical roadmap.

Lead, Site Reliability Engineering – AI Accelerator Infrastructure

LLM Engineer

• Identify and prototype emerging LLM inference use cases suited to heterogeneous hardware deployments.
• Build compelling proof-of-concept systems that demonstrate D-Matrix capabilities to customers, partners, and internal stakeholders.
• Develop and tune custom kernels and operator-level optimizations to maximize throughput and minimize latency.
• Drive quantization, sparsity, and batching strategies tailored to D-Matrix computational model.
• Build and maintain inference runtimes, serving frameworks, and evaluation tooling.
• Contribute to distributed inference systems: tensor/pipeline parallelism, disaggregated prefill/decode, KV-cache management.
• Work closely with hardware architects to provide firmware and compiler teams with actionable inference workload insights.
• Partner with product and business development to translate POCs into customer-facing demonstrations.
• Contribute to technical publications, whitepapers, and open-source projects that advance D-Matrix visibility.

Principal LLM Inference Engineer

AI Research Scientist

• Invent, design, and implement efficient algorithms
• Optimize large language model inference on DNN accelerators
• Work as part of a close-knit team of mathematicians, ML researchers, and ML engineers
• Create and apply advanced algorithmic and numerical techniques

Senior Staff ML Researcher – LLM Algorithmic Optimization

Full-stack Engineer

• Own and maintain design and DFT flows
• Develop scalable automation infrastructure and scripting solutions
• Support DFT-related flows including SPF extraction, ATPG pattern generation, comp mode WRP, etc.
• Support EDA tool deployment, integration, and user enablement

Senior Staff Engineer, CAD – Flow

SDET

• Design, build, and maintain scalable automated test frameworks for kernel validation across simulation, emulation, and silicon targets.
• Develop correctness and performance regression suites covering ML operators.
• Implement testing pipelines integrated into CI/CD workflows.
• Drive alignment on test strategy, coverage, and release readiness.
• Act as the primary liaison between the Kernels engineering team and the QA organization.

Staff Software Engineer in Test – SDET

• Be part of the team that helps productize the SW stack for our AI compute engine.
• Responsible for the development, enhancement, and maintenance of software kernels for next-generation AI hardware.
• Build software deliverables in a tight development window.
• Work with a team of compiler experts to build out the compiler infrastructure, collaborating closely with other software and hardware experts.

Principal Software Engineer – Kernels

Software Engineer

• Drive end-to-end NPI execution from Concept through EVT, DVT, PVT, and MP across multiple concurrent programs.
• Own systems-level architectural sign-off and engineering change control for cards, trays, and rack platforms.
• Build and lead the NPI engineering org — board/system HW design, FPGA design.
• Support hyperscaler customer engagements at the technical layer — design wins, PoCs, and integration deep-dives.
• Define the validation matrix per program and drive risk burn-down through a clean hand-off to production ramp.

Director, Systems NPI Engineering

Program Manager

• Lead cross-functional manufacturing programs from concept through end-of-life, owning schedule, scope, cost, and risk.
• Drive build planning and execution for EVT, DVT, PVT, and MP phases at contract manufacturer sites.
• Define and track exit criteria for each NPI phase, including yield, cycle time, FPY, and quality gates.
• Maintain integrated program schedules and identify critical path dependencies across hardware, firmware, tooling, and supply readiness.
• Own the Manufacturing Readiness Plan (MRP), including process flow, station design, fixture and tooling readiness, test coverage, and operator training.
• Partner with Manufacturing Engineering to validate process capability (Cpk), drive DFM/DFA feedback into Engineering, and qualify production lines.
• Lead production ramp, monitor key KPIs (yield, throughput, RTY, scrap, WIP), and drive corrective actions when targets are missed.
• Coordinate ECO/ECN implementation at the factory and ensure clean cut-in with minimal disruption to output.
• Partner with Commodity Managers and Planning to align material availability, lead times, and clear-to-build status with build plans.
• Drive capacity assessments and ensure CM line, equipment, and labor capacity meet forecasted demand.
• Identify supply risks early, develop mitigation plans, and escalate constraints to leadership with clear options and recommendations.
• Partner with Quality to drive failure analysis, 8D problem solving, and closed-loop corrective actions on field and factory issues.
• Lead yield improvement initiatives and cost-down projects across the product lifecycle.
• Champion continuous improvement, lean manufacturing, and Six Sigma practices on the production floor.
• Serve as the primary day-to-day operational point of contact with contract manufacturers and key suppliers.