---
title: 'Senior Staff Inference Performance Engineer at d-Matrix'
canonical: 'https://feeny.ai/job/senior-staff-inference-performance-engineer-d-matrix-santa-clara-bwd8va6rtmg4'
type: 'job'
last_seen: '2026-10-16'
---

# Senior Staff Inference Performance Engineer at d-Matrix

- **Company:** d-Matrix
- **Location:** Santa Clara, CA
- **Compensation:** $175k–$265k
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-10-15
- **Last confirmed live:** 2026-10-16
- **Apply:** https://jobs.ashbyhq.com/d-matrix/f637e097-d12a-4d0c-afd9-fc5f355ad27d

## Job description

At d-Matrix, we are focused on unleashing the potential of generative AI to power the transformation of technology. We are at the forefront of software and hardware innovation, pushing the boundaries of what is possible. Our culture is one of respect and collaboration. We value humility and believe in direct communication. Our team is inclusive, and our differing perspectives allow for better solutions. We are seeking individuals passionate about tackling challenges and are driven by execution.  Ready to come find your playground? Together, we can help shape the endless possibilities of AI. Senior Staff Inference Performance Engineer Location: Santa Clara, CA / Remote, US

## Role Overview

The Inference Cloud Engineering team builds the deployment and orchestration technology behind d-Matrix’s inference services: an internal cloud where teams test and tune models, and a customer-facing Cloud with self-service inference endpoints and compute. As the team’s Inference Performance Engineer, you will own end-to-end performance of the workloads we deploy, from the moment a request arrives to the moment a result is returned. The standard is that a workload on our orchestrated platform should perform at least as well as it does on bare metal. Today’s workloads include speculative decoding and attention-FFN disaggregation across d-Matrix Corsair accelerators and GPUs, with more heterogeneous architectures coming. Because there is no fixed system to master, the job is a method: profile first, form a hypothesis, test it, and then change the system. You will own the outcome, not every fix. Many root causes sit with other teams, so you will fix what you understand well and hand off the rest with evidence the owning team can act on.

## What You Will Do

- Diagnose performance problems across the full serving path, from orchestration (scheduling, placement, networking, autoscaling) to inference internals (batching, KV-cache, prefill/decode, serving framework, driver and runtime, interconnect, host OS and NUMA, accelerator).
- Isolate each problem to a specific layer and owner, then decide whether to fix it directly, route it to the owning team, or both, with a workaround now and a tracked handoff for the permanent fix.
- Write minimal, reproducible problem statements for cross-stack findings so owning teams can act without repeating the investigation.
- Protect throughput, latency, and stability targets for orchestrated workloads by finding and closing gaps against bare metal, such as placement overhead, non-performance power defaults, and extra network hops.
- Assess what it takes to scale from single deployments to fleet operation, including routing, placement, and shared-resource contention.
- Capture each workload’s node requirements (CPU placement, memory and NUMA locality, network path) in the orchestration layer’s configuration so performant deployment is the default.
- Build lightweight telemetry and benchmarks that reach into prototype stacks to isolate or hand off problems.
- Turn recurring investigations into playbooks and mentor engineers in the profiling-first method.

## What You Will Bring

- 8+ years of hands-on performance or systems engineering, including resolving hard regressions that crossed multiple layers of a stack.
- Track record of finding performance overhead through profiling in unfamiliar, sparsely documented systems, valued more than experience with any specific vendor stack or accelerator.
- Deep systems fundamentals, including Linux internals, NUMA, CPU pinning and cpusets, PCIe, memory and cache behavior, and network paths.
- Experience running performance-sensitive workloads on Kubernetes, including identifying when scheduler defaults, network overlays, or orchestration abstractions cost latency or throughput, and closing the gap.
- Working knowledge of LLM inference serving, including batching, KV-cache, prefill/decode, quantization, and speculative decoding.
- Proficiency in Python and C/C++, sufficient to instrument, debug, and patch code across the stack.
- Clear technical writing that hardware, firmware, or platform teams can act on without context from your part of the stack.
- Sound judgment about ownership, with examples of correctly handing off problems that were not yours to fix.
- Fluency with AI and agentic tools for investigation, code search, log triage, and drafting instrumentation, with the discipline to verify output against real data.

## Preferred Qualifications

- Experience with LLM serving frameworks such as vLLM, SGLang, or TensorRT-LLM.
- Hands-on experience building or tuning speculative decoding, disaggregated serving, or heterogeneous serving architectures.
- Experience tuning KV-cache management, request and batch scheduling, or weight prefetch and residency in an LLM serving system.
- GPU programming and profiling experience (such as CUDA, Nsight, NCCL), valued as transferable background.
- Experience with pre-production or bring-up hardware, or in organizations where root causes routinely cross team boundaries.
- Rust experience.
- Startup experience or comfort in environments where priorities shift quickly.

## Equal Opportunity Employment Policy

d-Matrix is proud to be an equal opportunity workplace and affirmative action employer. We’re committed to fostering an inclusive environment where everyone feels welcomed and empowered to do their best work. We hire the best talent for our teams, regardless of race, religion, color, age, disability, sex, gender identity, sexual orientation, ancestry, genetic information, marital status, national origin, political affiliation, or veteran status. Our focus is on hiring teammates with humble expertise, kindness, dedication and a willingness to embrace challenges and learn together every day. d-Matrix does not accept resumes or candidate submissions from external agencies. We appreciate the interest and effort of recruitment firms, but we kindly request that individual interested in opportunities with d-Matrix apply directly through our official channels. This approach allows us to streamline our hiring processes and maintain a consistent and fair evaluation of al applicants. Thank you for your understanding and cooperation.

## About d-Matrix

## Company Overview
- **One-liner**: d-Matrix is building ultra-low latency, memory-centric AI inference hardware and software platforms for datacenter-scale generative AI workloads.
- **Entity Type**: Private (Series C, total raised ~$429M–$450M per conflicting reports)
- **Headquarters**: Santa Clara, California, USA
- **Founded**: 2019
- **Founders**: Sid Sheth (CEO) & Sudeep Bhoja (CTO / Founder)

## Core Business
- **Primary industries**: AI infrastructure, semiconductor / hardware acceleration, datacenter compute
- **Target customers**: Cloud providers, enterprises running large-scale generative AI inference (B2B)
- **Mission / purpose**: To transform AI from unsustainable to attainable by breaking through limits of latency, cost, and energy in inference.

## Products & Services
- **Corsair™** – AI inference accelerator platform (PCIe form factor, chiplet-based, 3D stacked DRAM) purpose-built for the decode phase of disaggregated inference. Works alongside GPUs for low-latency interactive AI.
- **JetStream™** – Purpose-built I/O accelerator for AI inference (networking fabric to scale accelerator-to-accelerator communication).
- **Aviator** – Software stack that orchestrates and optimizes inference workloads on d-Matrix hardware.
- **SquadRack™** – Industry’s first rack-scale, disaggregated standards-based solution for AI inference, built with infrastructure partners.

## Market Standing
- **Valuation**: Not publicly disclosed (private company)
- **Key metric**: Total funding – $429M (per CB Insights) or $450M (per company blog after $275M Series C). Series C announced in late 2025 / early 2026.
- **Notable investors**: Temasek, M12 (Microsoft’s venture arm), Playground Global, Nautilus Venture Partners, Industry Ventures, Mirae Asset Financial Group, Triatomic Capital, Bullhound Capital.
- **Growth signals**:
  - Corsair entered full production in June 2026.
  - Won “AI Processor Innovation Award” from AI Breakthrough in June 2026.
  - Filed 21+ patents in parallel computing, neural networks, NLP.
  - Opened engineering offices in Santa Clara, Toronto, Bengaluru, Sydney, and Belgrade – global expansion underway.

## Competitive Advantages
- **Memory-centric compute architecture (3DIMC™)** that eliminates latency bottlenecks caused by traditional memory-bound AI inference.
- Chiplet-based design enables scaling to 100B+ parameter models in a PCIe form factor.
- Disaggregated, standards-based rack-scale approach (SquadRack) that integrates seamlessly with existing datacenter infrastructure.
- Team of industry veterans who have shipped over 100 million chips and generated $5B+ in prior revenue.

## Strategic Focus
- Scaling production of Corsair to meet customer demand for agentic AI workloads (voice agents, coding tools, real-time inference).
- Building a heterogeneous compute ecosystem where d-Matrix accelerators complement GPUs rather than replace them.
- Expanding software stack (Aviator) and networking (JetStream) to deliver full-stack inference solutions.

## Why Work Here
- **Culture**: “Round pegs in square holes” – builders, innovators, dreamers. Emphasis on humility, direct communication, and collaboration.
- **Work model**: Remote & hybrid working model (global offices in Silicon Valley, Sydney, Bengaluru, Toronto, Belgrade).
- **Benefits**: Competitive pay and equity, health care, flexible time-off, paid paternity leave, 401k, on-site fitness centers, free food/snacks, peer coaching & development, team-building activities.
- **Engineering environment**: Work with world-leading engineers and researchers on cutting-edge AI hardware/software. Opportunity to shape the future of AI inference infrastructure.

## Sources
1. [d-matrix.ai – Homepage](https://www.d-matrix.ai/)
2. [d-matrix.ai – About / Leadership](https://www.d-matrix.ai/about/)
3. [d-matrix.ai – Careers](https://www.d-matrix.ai/careers/)
4. [d-matrix.ai – Corsair Production & AI Breakthrough Award](https://www.d-matrix.ai/announcements/d-matrix-corsair-ai-inference-platform-enters-full-production-to-meet-customer-demand/)
5. [CB Insights – d-Matrix Company Profile](https://www.cbinsights.com/company/d-matrix)
6. [Ashby – d-Matrix Jobs](https://jobs.ashbyhq.com/d-matrix)

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