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We are team of chip design, analog and AI domain experts working towards increasing
Generative AI adoption by leveraging novel in-memory compute hardware to vastly enhance
the power efficiency of model deployment at the edge. We are building something entirely
new to make AI ubiquitous in a responsible way – widely applicable, economically viable,
and environmentally sustainable.
About the Role
The AI Framework Architect is a tech lead role building the highest level of the compiler stack,
where models are ingested from PyTorch/ONNX/Keras and converted to a proprietary
analog graph that can be parsed by the lower levels of the stack for hardware deployment.
The role requires simultaneous tech lead and individual contributor (IC) work hats since the
development team is highly skilled and motivated, but the complexity of the compiler
requires deep expertise in graph, deep learning and software engineering principles to
overcome hurdles presented by the novel chip architecture. You need to write code
shoulder-to-shoulder with your team.
Responsibilities
As the tech lead for the AI framework, you will be responsible for these key facets of model
deployment:
• Compiler Integration: continue to build and integrate Python-based functionality to
ingest, parse and prepare model deployment to hardware
• Analytical Modeling: understand QAT, PTQ and analog-related modeling principles
• Deep Learning: understand at a fundamental level how these models/networks are
defined to train them for our specific workload requirements
• Graph Computation: fully comprehend at an operational level to direct graph
conversion processes at lower levels of the compiler stack
• Team Development: the individual will lead a diverse, highly talented, motivated,
remote team of engineers, and must be invested not only in product deliverables, but
also in team members' growth in terms of their professional and technical skill sets.
Candidate Requirements
The candidate will have:
• Python: 5+ years in Python development experience as an IC
• Tech Lead: have led a team of engineers in developing production-level
deliverables in deep learning/AI
• Software Engineering: understand how to manage production workflows via
Git/BitBucket and how to direct development efforts with Jira tasking
• Compilers: have experience working on production or proprietary compilers
• Deep Learning: have built and trained DL pipelines for models in either computer
vision or NLP domain, using one or multiple DL frameworks such as PyTorch,
• Analytics: have an established background working on quantization techniques,
stochastic processes and/or advanced numerical principles
Ideally, the candidate will have:
• Python: 8+ years in Python development
• Publication Track Record: published papers in the DL/AI in conferences or
journals, and/or holding pertinent patents
• AI Accelerators: have prior work history with other AI accelerator platforms such as
Location & Commitments
We are on a hybrid work schedule, requesting two days a week in office (Santa Clara)
presence with the remaining work week being operated remotely. The hours are challenging
since the development team is global, with members working from Germany, Australia and
Sri Lanka. There is flexibility on the in-office presence requirement, but the tech lead role is
essential for many facets of the company and needs to be readily available for meeting
sessions during PST work hours.
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