AI Systems Architect
Velaura AI develops ultra-low-power compute technology for cloud, edge, and physical AI applications. It also offers Teraflux Bitcoin mining hardware, fleet-management software, and related support for mining operators.
Funding history
Projects
About Velaura AI
Velaura AI is a semiconductor and technology company that provides patented ultra-low-power silicon design technology, IP, toolflows, and custom chiplet solutions for AI compute platforms. Its customers include hyperscaler and XPU companies seeking reduced power consumption and higher compute efficiency. The company also builds Teraflux Bitcoin mining products, including air-, hydro-, and immersion-cooled miners, ASICs, modular containers, miner firmware, fleet-management software, and enterprise customer support.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You analyze modern AI model architectures, evaluate their computational and system requirements, and determine how they map to specialized hardware. You translate model requirements into efficient silicon implementations, optimize models and dataflows, develop performance and efficiency models, and collaborate across software, algorithms, and hardware disciplines.
Requirements
- 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 with ML frameworks such as PyTorch, JAX, or TensorFlow
- 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
- Experience with hardware-software co-design or AI accelerator architecture
- Familiarity with quantization, sparsity, pruning, or distillation
- Experience implementing or optimizing AI models for specialized hardware platforms
- Exposure to emerging AI model architectures beyond transformers
- Experience with robotics, autonomous systems, or embodied AI applications
Responsibilities
- Analyze modern AI model architectures including transformers and emerging alternatives
- Evaluate model suitability for different application domains
- Translate model requirements into efficient silicon implementations
- Identify opportunities to optimize models, algorithms, and dataflows for performance, efficiency, and scalability
- Understand training and inference pipelines and identify implications for hardware design
- Develop performance and efficiency models to guide architectural decisions
- Collaborate with software and hardware teams to deploy models efficiently on new compute platforms
- Stay current with emerging AI model research
Benefits
- Performance-based incentives
- Equity participation
- Medical coverage
- Dental coverage
- Vision coverage
- Paid time off
- Flexible work arrangements
- Professional development opportunities