Hardware is bottlenecked by data movement and compute. At Luminous Computing, we use photonics to alleviate those bottlenecks. Our goal is t...
Hardware is bottlenecked by data movement and compute. At Luminous Computing, we use photonics to alleviate those bottlenecks. Our goal is to create a single AI training and inference chip that will outperform the world's largest supercomputer. Backed by Bill Gates, Luke Nosek, Ali Patorvi, Dara Khosrowshahi, and other reputable Silicon Valley investors.
About the job
The AI team is a long-term mission/vision/research team focused on developing system architectural innovations and software innovations that leverage the drastic new capabilities of photonics hardware. As a member of the AI team, the guiding goal is to drive the co-evolution of hardware, software, and algorithms for the next generation of AI models. Although the questions that the AI team is answering are focused on the long term, the expectation is their research will also produce short-term and intermediate answers, and for those short-term answers to inform the design of our first AI products, including the demo, prototype, and production chips.
As a machine learning engineer/researcher you will support the development of target models and algorithms as part of the ML team. You will assist in the evaluation and analysis of future models running on existing hardware to gauge where the pinch points exist. You will work to add these experimental models to the suite of test models for the ML projects. You will investigate the efficacy of current leading edge research as part of the ML team.
As part of the Luminous Computing ML team, you will also be responsible for contributing to the implementation of both benchmark executables and demonstration software for our various prototypes and product hardware.
- Assisting the research direction and experimentation of the teams search for the next generation of AI models
- Regular literature review to keep up with state-of-the-art methodologies and the implications on the hardware to support it
- Identifying bottlenecks in current ML deployments to dictate architectural design
- Developing the infrastructure for a benchmark suite as well as experimentation
- Running the operational experiments to collect the empirical results to drive decision making in the ML team.
- Design documentations and design reviews.
- Work closely with architecture, software, hardware, and modeling teams to ensure agile developments and design convergence.
- BS/MS/PhD in CS, Math, or Physics
- Past deep learning publication(s)
- Strong math backgrounds
- Proficiency with DL research code
- Proficiency in either Tensorflow or Pytorch or other ML specification platform.
- Good communication skills and willingness to work with others.
Luminous Computing provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, or genetics. In addition to federal law requirements, Luminous abides by applicable state and local laws governing nondiscrimination in employment. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.
Note to Recruitment Agencies: Luminous Computing does not accept unsolicited agency resumes. Furthermore, Luminous Computing does not pay placement fees for candidates submitted by any agency other than its approved partners.