AMS Design Engineer
Listed on 2026-02-16
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Engineering
Systems Engineer, Electronics Engineer
About Celestial AI
As Generative AI continues to advance, the performance drivers for data center infrastructure are shifting from systems-on-chip (SOCs) to systems of chips. In the era of Accelerated Computing, the data center bottlenecks are the system’s interconnect bandwidth, memory bandwidth, and memory capacity. Celestial AI’s Photonic Fabric™ is the next-generation interconnect technology that delivers a tenfold increase in performance and energy efficiency compared to competing solutions.
The Photonic Fabric™ is available to our customers in multiple technology offerings, including optical interface chiplets, optical interposers, and Optical Multi-chip Interconnect Bridges (OMIB). This allows customers to easily incorporate high bandwidth, low power, and low latency optical interfaces into their AI accelerators and GPUs. The technology is compatible with standard 2.5D packaging processes, enabling XPUs to utilize optical interconnects for both compute-to-compute and compute-to-memory fabrics, achieving bandwidths in the tens of terabits per second with nanosecond latencies.
This innovation empowers hyperscalers to enhance the efficiency and cost-effectiveness of AI processing by optimizing the XPUs required for training and inference, while significantly reducing the TCO. Celestial AI is developing a Photonic Fabric ecosystem consisting of tier-1 partnerships that include custom silicon/ASIC design, system integrators, HBM memory, assembly, and packaging suppliers.
About the RoleWe are building next-generation 50G/100G optical link solutions for data-centric computing, leveraging advanced silicon photonics integrated with cutting-edge CMOS electronics. We’re looking for a highly skilled Senior AMS Design Engineer to architect and implement high-speed analog and mixed-signal circuits for our photonic transceivers and electronic ICs (EICs).
You’ll work closely with a multidisciplinary team across photonics, system, packaging, and validation to deliver scalable, low-power, high-performance EICs for optical compute and interconnects.
Essential Duties and Responsibilities- Top-down architectural analysis of AMS systems.
- Develop understanding of the digital and photonics subsystem and associated requirements on the AMS sub system.
- Utilize knowledge of high-performance analog design and compare various topologies to support AI application requirements.
- Enhance system performance using digitally assisted analog techniques and appropriate partitioning of analog and digital circuits.
- Drive transistor-level feasibility study for various AMS circuits.
- Define design specifications and verification plans.
- Define production and bench-level test plans.
- Requires Master’s Degree or PhD in related areas of expertise.
- 10+ years of experience AMS Design.
- Experience with architecture, design, and production expertise in high-speed data converters and ultra-low-power analog circuits.
- Data converter architectures and design trade-offs; low-power and high-precision analog techniques.
- Architect circuit solutions that address noise, linearity, power consumption, and silicon area requirements.
- AMS design flows and chip assembly techniques; experience with collaborating with design, layout, and production test engineers.
- Excellent communication skills to work with multiple domain experts (digital/VLSI, AI/ML, Photonics, and packaging).
As an early stage startup, we offer an attractive total compensation package including base salary, bonus, and equity. The target base salary for this role is approximately $ - $, with possible variation based on depth of experience and skills demonstrated during interviews.
We offer great benefits (health, vision, dental, and life insurance) and a collaborative, learning-oriented work environment with colleagues engaged in developing the next generation of high-performance computing architecture.
Celestial AI Inc. is proud to be an equal opportunity workplace and an affirmative action employer.
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