Full-Time

Staff Analog Design Engineer

TX/RX Datapath

Posted on 8/19/2026

d-Matrix

d-Matrix

201-500 employees

Delivers memory-integrated AI compute platforms

Compensation Overview

$155k - $250k/yr

Santa Clara, CA, USA

Hybrid

Hybrid work arrangement in Santa Clara.

Bachelor's, Master's, PhD

Category
Hardware Engineering (2)
,
Required Skills
Python
MATLAB

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Requirements
  • A Bachelor of Science, Master of Science, or Doctor of Philosophy degree in Electrical Engineering is required, along with 8 or more years of hands-on analog and mixed-signal circuit design experience.
  • Ownership of a SerDes transmit or receive datapath block through working silicon in a high-speed link is required.
  • Deep knowledge of high-speed driver design, receive front-end design, and equalization is required, with practical familiarity with adjacent clocking and clock-data recovery blocks.
  • Practical command of jitter and noise analysis, including decomposition, budgeting, and simulation methods for quantifying contributors, is required.
  • Circuit design experience in advanced FinFET or GAA process nodes is required.
  • Hands-on use of industry-standard analog design and simulation tools and methodologies, including Cadence Virtuoso, Spectre, Monte Carlo and corner analysis, and post-layout simulation, is required.
  • Experience with link and channel modeling, including MATLAB, Python, and S-parameter models, is required.
  • Silicon bring-up and bench debugging experience with high-speed laboratory equipment such as oscilloscopes and bit error rate testers is required.
Responsibilities
  • Own transistor-level design of the SerDes transmit path, including output drivers using SST and/or CML, pre-driver and serializer stages, and transmit-side feed-forward equalization.
  • Own transistor-level design of the receive front-end, including termination and ESD-aware input networks, continuous-time linear equalization, variable-gain amplifiers, samplers, and applicable analog-to-digital converter-based front-ends.
  • Design and verify the equalization path, including decision-feedback equalization and feed-forward equalization architecture, tap resolution, and adaptation behavior, and own the associated architectural trade study.
  • Derive block-level specifications from link budgets covering insertion loss, crosstalk, reflection, jitter, and bit error rate targets, and defend those specifications in design reviews.
  • Build verification environments for circuit blocks, including testbenches, process-voltage-temperature corner coverage, six-sigma Monte Carlo analysis, transient-noise analysis, and post-layout back-annotated simulation.
  • Provide behavioral and Verilog-A models for full-chip verification and support backend engineers through integration.
  • Perform link and channel modeling in MATLAB, Python, or equivalent, including S-parameter channel and package models, statistical eye and bit error rate analysis, and equalization trade studies.
  • Drive layout of circuit blocks in deep sub-micron process nodes, collaborating with layout engineers on floorplanning, matching, shielding, current density, and parasitic control.
  • Co-design with package and signal-integrity engineers on bump maps, escape routing, and channel budgets.
  • Contribute to testboard design and take circuit blocks through silicon bring-up and bench characterization, correlating measured performance against simulation.
Desired Qualifications
  • Die-to-die interconnect experience with UCIe, BoW, or a proprietary die-to-die PHY, including short-reach and low-energy-per-bit link constraints.
  • Experience with PAM4 signaling and digital signal processing-based receiver architectures, including analog-to-digital converter-based front-ends.
  • Familiarity with UCIe, OIF CEI-112G/224G, IEEE 802.3, and PCIe Gen6/Gen7 specifications.
  • Experience porting a datapath block across process nodes.
  • Experience generating IBIS-AMI models or developing SerDes automatic test equipment and production tests.
  • Participation in or contributions to standards bodies.

d-Matrix provides scalable, modular AI compute hardware and software for large datacenters, prioritizing energy efficiency and reduced data movement. Its core DIMC engine embeds compute directly into programmable memory, while a fabric of low-power chiplets delivers configurable compute resources and the accompanying software optimizes performance. This combination cuts data transfers and power use, aligning hardware design with memory-based computation for AI inference. The goal is to let large datacenters run AI workloads more efficiently at scale with customizable, modular compute platforms.

Company Size

201-500

Company Stage

Series C

Total Funding

$429M

Headquarters

Santa Clara, California

Founded

2019

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Simplify Jobs

Simplify's Take

What believers are saying

  • Corsair entered full production by June 2026 and ships to priority customers.
  • Parasail deployed Corsair with Hopper and Blackwell in July 2026, validating heterogeneous inference.
  • d-Matrix raised $275 million in November 2025, backing expansion and IPO preparation.

What critics are saying

  • Corsair only accelerates smaller inference workloads; trillion-parameter reasoning stays NVIDIA territory.
  • Two acquisitions in four months create integration drag and distract engineering through 2027.
  • If Blackwell and custom ASICs close inference efficiency gaps, d-Matrix becomes a niche software bundle.

What makes d-Matrix unique

  • Corsair's DIMC chiplet architecture keeps compute near memory, targeting inference latency and energy.
  • August 2026 Wallaroo acquisition adds orchestration software, completing d-Matrix's silicon-to-stack inference platform.
  • April 2026 GigaIO deal adds rack-scale fabric, enabling heterogeneous GPU-XPU deployments.

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Benefits

Hybrid Work Options

Growth & Insights and Company News

Headcount

6 month growth

0%

1 year growth

-1%

2 year growth

0%
Business Wire
Aug 13th, 2026
Infinity's AI agent makes chips inference-ready in days, achieving alternative to CUDA in weeks

Infinity has developed agentic tools that make AI chips inference-ready within days, drastically reducing the typical months-long process. The company's autonomous agent, Ignition, automatically generates and optimises low-level compute kernels, compilers and SDKs that determine chip efficiency. In a case study with d-Matrix for its Corsair inference accelerator, Infinity reached 92% of theoretical peak performance within 10 hours of hardware access and had three frontier models running end-to-end within 10 days. The breakthrough addresses a key bottleneck in AI chip adoption: the absence of mature software stacks like Nvidia's CUDA, which took 20 years to develop. Founded in August 2025 and headquartered in San Francisco, Infinity raised $15 million in seed funding from Touring Capital and angel investors.

IT Digest
Aug 4th, 2026
d-Matrix Acquires Wallaroo.ai to Accelerate AI Deployment.

d-Matrix Acquires Wallaroo.ai to Accelerate AI Deployment. Second acquisition in four months brings ease of deployment and orchestration expertise to d-Matrix's silicon-to-software data center inference stack d-Matrix, the pioneer in ultra-low-latency AI inference for data centers, announced the acquisition of Wallaroo.ai, a leader in AI inference deployment and orchestration software. The acquisition brings d-Matrix the technology platform, intellectual property, and expert engineering talent of Walaroo.ai. The integration of Wallaroo follows the acquisition of GigaIO's data center business in April, and further advances d-Matrix as a category leader for rack-scale heterogeneous AI solutions that pair GPUs with specialty XPUs to achieve maximum speed and energy efficiency. With Wallaroo, d-Matrix now offers an end-to-end inference platform spanning high-performance silicon to deployment software making it easy for customers to deploy and scale low-latency inference from single-server nodes to multi-rack data center scale. The members of Wallaroo's engineering, product, and go-to-market teams joining d-Matrix bring deep expertise in software architecture, high-performance computing, Kubernetes operations, and AI inference systems. "Our customers are deploying AI inference across increasingly complex, heterogeneous environments and they've told us the biggest barrier isn't just performance, it's also the operational complexity of getting there," said Sid Sheth, founder and CEO of d-Matrix. "Wallaroo solves that. By integrating deployment and orchestration software directly into our stack, we're giving customers the simplest, fastest path from evaluation to production-scale inference. We believe AI infrastructure should expand intelligence while expanding efficiency and that starts with making it effortless to deploy." "What drew us to d-Matrix was our shared belief that inference requires seamless deployment and scale, not just faster chips," said Vid Jain, Founder and CEO of Wallaroo.AI. "Combining our AI orchestration software with d-Matrix's purpose-built silicon immediately creates an inference platform that's leaps and bounds ahead of the market. We're thrilled to join a company with this level of vision and execution, as well as with an extraordinary culture. We're very excited to build the future together."

PR Newswire
Aug 3rd, 2026
d-Matrix acquires Wallaroo.ai to simplify deployment of AI inference workloads

d-Matrix has acquired Wallaroo.ai, a leader in AI inference deployment and orchestration software. This marks d-Matrix's second acquisition in four months, following the purchase of GigaIO's data center business in April. The acquisition brings Wallaroo's technology platform, intellectual property, and engineering talent to d-Matrix. It enables d-Matrix to offer an end-to-end inference platform spanning high-performance silicon to deployment software, supporting deployment from single-server nodes to multi-rack data center scale. d-Matrix's flagship Corsair inference platform is now in full production and shipping to priority customers. In early July, d-Matrix and Parasail announced the deployment of Corsair alongside NVIDIA Hopper and Blackwell GPU architectures in Parasail's cloud data center. The company is hiring engineers across several speciality areas to support its continued growth.

PR Newswire
Jul 8th, 2026
Parasail deploys d-Matrix Corsair accelerators with NVIDIA GPUs for 10x faster AI inference

Parasail is deploying d-Matrix Corsair inference accelerators alongside NVIDIA Hopper and Blackwell GPUs to deliver up to 10 times faster, more cost-efficient inference services to customers. The deployment marks one of the first commercial-scale examples of heterogeneous disaggregated inference in production. The approach combines NVIDIA GPUs for compute-intensive prefill with d-Matrix Corsair accelerators for latency-sensitive decode. Parasail's automatic kernel optimisation technology dynamically routes workloads to appropriate hardware to maximise performance across its heterogeneous fleet. D-Matrix Corsair's performance stems from its Digital In-Memory Compute chiplet architecture, which integrates compute with memory on the same silicon, enabling up to 10 times faster interactive inference and up to three times better energy efficiency versus traditional approaches. The companies plan to share detailed performance results following initial deployments across Parasail's global fleet of over 40 data centres in 15 countries.

PR Newswire
Jun 25th, 2026
d-Matrix Corsair wins AI Breakthrough Award for blazing fast token generation with GPUs

d-Matrix has announced its Corsair inference accelerator won the 2026 AI Breakthrough Award for "AI Processor Innovation". The Santa Clara-based company's platform was recognised for its ability to work alongside GPUs in heterogeneous compute environments, delivering significant increases in AI interactivity. Corsair, which entered full production this month, is purpose-built for the decode phase of disaggregated inference. The system addresses latency demands from agentic AI workloads, including real-time voice agents and interactive coding tools, whilst working with GPUs to handle compute-intensive tasks. Founded seven years ago, d-Matrix specialises in low-latency AI inference for data centres. The AI Breakthrough Awards programme, now in its ninth year, received over 5,000 nominations from companies across more than 20 countries.