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AI Systems Architect; Models & Hardware Co-Design

Job in Santa Clara, Santa Clara County, California, 95053, USA
Listing for: Velaura
Full Time position
Listed on 2026-06-07
Job specializations:
  • IT/Tech
    AI Engineer (Applied/Software), Systems Engineer, Machine Learning/ ML Engineer, Artificial Intelligence
Salary/Wage Range or Industry Benchmark: 120000 - 160000 USD Yearly USD 120000.00 160000.00 YEAR
Job Description & How to Apply Below
Position: AI Systems Architect (Models & Hardware Co-Design)

Location: Bay Area (Onsite or Hybrid)

About Velaura AI

Velaura AI is building the next generation of compute platforms for artificial intelligence. As AI expands beyond the cloud into edge systems and physical environments
, the constraints of energy efficiency, latency, and system architecture are becoming fundamental.

A particularly exciting frontier is physical and embodied AI
—systems that perceive, reason, and act in the real world. Applications such as robotics, autonomous mobile robots (AMRs), drones, and other intelligent machines demand new approaches to compute that combine real-time responsiveness, energy efficiency, and advanced AI capabilities.

Our mission is to design silicon and systems from first principles to enable these emerging classes of AI applications. Velaura combines deep semiconductor expertise with hardware–software co-design to deliver breakthrough performance per watt across cloud, edge, and embodied AI workloads.

We are assembling a small, world-class team of researchers, architects, and engineers to rethink the foundations of AI compute.

Role Overview

We are looking for an AI Systems Architect who sits at the intersection of machine learning models and hardware architecture
.
In this role, you will work across model development, algorithms, and hardware architecture to identify and shape the AI workloads that will define the next generation of compute platforms.

You will evaluate emerging model architectures, understand their training and inference characteristics, and help translate them into efficient hardware implementations.

This role requires someone who is comfortable moving between mathematical models, software frameworks, and hardware architecture
, and who enjoys solving problems at the boundary between disciplines.

Responsibilities
  • Analyze modern AI model architectures including transformers and emerging alternatives to understand their computational and system requirements.
  • Evaluate model suitability for different application domains and help determine which model architectures are best matched to specific workloads.
  • Work closely with hardware architects to translate model requirements into efficient silicon implementations.
  • Identify opportunities to modify or optimize models, algorithms, or dataflows to improve performance, efficiency, or scalability in hardware.
  • Understand training and inference pipelines for modern AI models and identify implications for hardware design.
  • Develop performance and efficiency models to guide architectural decisions.
  • Collaborate with software and hardware teams to ensure that models can be deployed efficiently on new compute platforms.
  • Stay current with emerging AI model research and identify opportunities where new architectures may benefit from specialized hardware.
Required Qualifications
  • Strong understanding of modern machine learning architectures, including transformers and related model families.
  • Solid grounding in the mathematical foundations of machine learning, optimization, and deep learning algorithms.
  • Experience working with ML frameworks such as PyTorch, JAX, or Tensor Flow.
  • Ability to analyze model computation graphs and translate them into efficient dataflows and compute patterns.
  • Experience with AI model training and inference workflows.
  • Strong systems thinking and ability to work across software, algorithms, and hardware.
Preferred Qualifications
  • Experience with hardware–software co-design or AI accelerator architecture.
  • Familiarity with model optimization techniques such as quantization, sparsity, pruning, or distillation.
  • Experience implementing or optimizing AI models for specialized hardware platforms.
  • Exposure to emerging AI model architectures beyond transformers (e.g., world models, continuous-time networks, reinforcement learning systems).
  • Experience working with robotics, autonomous systems, or embodied AI applications.
Why Join Velaura

You will work on problems at the frontier of AI systems and compute architecture, helping shape how the next generation of AI models—especially those operating in the physical world—is translated into silicon.

This is an opportunity to work with a small team of experienced builders who have…

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