Base Salary
$195k - $285k/yr
Responsibilities
- Identify and prototype emerging LLM inference use cases suited to heterogeneous hardware deployments.
- Build compelling proof-of-concept systems that demonstrate D-Matrix capabilities.
- Develop and tune custom kernels and operator-level optimizations.
- 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 including tensor/pipeline parallelism.
- Work closely with hardware architects to provide actionable inference workload insights.
- Partner with product and business development to translate POCs into customer-facing demonstrations.
- Contribute to technical publications and open-source projects.
Requirements
- Bachelor’s degree in Computer Science, Electrical Engineering, or a related field with 10+ years of relevant experience.
- Master’s or PhD in a related field preferred, with 6+ years of industry experience.
- Strong proficiency in Python and C/C++.
- Hands-on experience optimizing LLM inference including attention kernels and quantization.
- Experience with at least one major inference framework at a contributor level.
- Familiarity with GPU kernel programming and performance profiling tools.
Benefits
- Work on genuinely novel hardware with unique inference optimization challenges.
- End-to-end ownership from idea to deployed system with a short feedback loop.
- Small, senior team with high autonomy and direct influence on product direction.
- Competitive compensation, equity, and benefits in Santa Clara, CA.
About d-Matrix
d-Matrix is an AI infrastructure company building the next generation of inference computing for the era of generative and agentic AI. Founded in 2019, d-Matrix is rethinking AI inference from the ground up with a full-stack approach spanning silicon, systems, networking, and software. Its flagship products, including the Corsair™ inference platform and JetStream™ inference fabric, are purpose-built to deliver high-performance, low-latency, and energy-efficient AI inference at datacenter scale. The company has raised nearly $500 million from a global syndicate of leading venture capital firms, sovereign wealth funds, and strategic investors, including Playground Global, Bullhound Capital, M12 (Microsoft’s Venture Fund), SK hynix, Temasek, Qatar Investment Authority, and Singapore’s EDBI. The company’s most recent financing valued d-Matrix at approximately $2 billion. As AI shifts from training to inference, the demands on AI infrastructure are changing. d-Matrix is building the infrastructure required to power the next generation of real-time AI at scale.