---
title: 'Sr. Staff ML Researcher, LLM Algorithmic Optimization at d-Matrix'
canonical: 'https://feeny.ai/job/sr-staff-ml-researcher-llm-algorithmic-optimization-d-matrix-santa-clara-t9ac7zgz45zh'
type: 'job'
last_seen: '2026-11-06'
---

# Sr. Staff ML Researcher, LLM Algorithmic Optimization at d-Matrix

- **Company:** d-Matrix
- **Location:** Santa Clara, CA
- **Compensation:** $175k–$265k
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-07-15
- **Last confirmed live:** 2026-11-06
- **Apply:** https://jobs.ashbyhq.com/d-matrix/59e6acf8-2d7c-4aa0-a2af-aa9f27d4d31e/application

**Skills:** Python, Object-Oriented Programming, Machine Learning, Large Language Models, DNN Accelerators, Transformer architecture

> Join the Algo team to invent, design, and implement efficient algorithms for optimizing large language model inference on DNN accelerators. This role involves applying advanced algorithmic and numerical techniques to cutting-edge research in mathematics, ML, and LLM applications.

## Job description

Join d-Matrix and help build the future of AI inference. We’ve pioneered a memory-centric architecture that brings compute directly into memory, making AI faster, more energy efficient, and accessible on a global scale. From chips and software to rack-scale systems, our team is tackling some of AI infrastructure’s hardest challenges — and shipping breakthrough technology today. If you want to create what comes next and help make infinite inference possible, we’d love to hear from you. Our culture is built on respect, collaboration, and direct communication. We value humility, we believe our different perspectives lead to better solutions, and we’re looking for people who are driven by execution and energized by hard problems.

## Role Overview

d-Matrix is seeking a Senior Staff ML Researcher to join our Algorithms team and develop new methods for running large language models efficiently on our DNN accelerators. This is a hands-on research role at the intersection of machine learning, applied mathematics, numerical computing, and AI hardware. You will invent, evaluate, and implement algorithmic techniques that improve LLM inference performance while preserving model quality, with a focus on challenges such as numerical precision, model compression, memory efficiency, and efficient execution on accelerator hardware. You will work closely with mathematicians, ML researchers, ML engineers, compiler engineers, and hardware architects to translate research ideas into practical solutions for cutting-edge generative AI workloads.

## What You Will Do

- Research and develop algorithmic and numerical techniques that improve the latency, throughput, memory efficiency, and accuracy of large language model inference on d-Matrix DNN accelerators.
- Design and evaluate methods such as low-precision quantization, model compression, sparsity, pruning, distillation, low-rank approximation, and other techniques for efficient neural-network execution.
- Optimize key transformer inference workloads, including matrix operations, attention mechanisms, and KV-cache utilization, based on model characteristics and hardware constraints.
- Analyze tradeoffs among model quality, numerical precision, memory footprint, compute efficiency, and system performance.
- Build high-quality research prototypes and evaluation frameworks in Python to test new ideas across relevant models, datasets, and workloads.
- Partner with hardware, compiler, and software teams to map algorithms effectively to accelerator capabilities, including supported data types, memory hierarchy, data movement, and compute architecture.
- Stay current with advances in efficient LLM inference, neural-network optimization, numerical methods, and hardware-aware machine learning, and apply relevant developments to d-Matrix products.

## What You Will Bring

- Master's degree or PhD in Computer Science, Mathematics, Statistics, Physics, Electrical Engineering, or a related quantitative field, with 5+ years of relevant hands-on experience.
- Strong foundation in machine learning and applied mathematics, with the ability to apply mathematical or numerical methods to practical ML problems.
- Hands-on experience developing and evaluating machine-learning algorithms, models, or research prototypes.
- Strong Python programming skills and experience with object-oriented code design.
- Experience with modern machine-learning frameworks such as PyTorch, JAX, or TensorFlow.
- Experience improving the performance, efficiency, or quality of machine-learning models through algorithmic or numerical techniques.
- Familiarity with neural-network architectures; experience with transformers, LLM inference, or hardware-aware ML optimization is advantageous but not required.
- Ability to design rigorous experiments, analyze results, and communicate technical findings clearly to cross-functional partners.

## 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 individuals 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 all 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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