sygaldry-technologies

AI Systems Performance Architect

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Older posting · still listed ·

  • onsite
  • FullTime
  • Technical
  • San Francisco
Work arrangement
onsite
Employment
FullTime
Stated compensation
USD 175,000–235,000 1 YEAR
Stated sponsorship
Not stated
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Requirements

2 with evidence7 unclear or unstated
Remote policy
onsite
“Provider workplace type: onsite”
From employer posting metadata
Minimum experience (years)
2
“PhD in Computer Engineering or Electrical Engineering with 2-5 years relevant work experience”
See matched passage in original description ↓
Employment type
FullTime
Compensation
USD 175,000–235,000 1 YEAR
7 fields not stated in this posting
Employer sponsorship
Not specified
Geographic scope
Not specified
Degree requirement
Not specified
Security clearance
Not mentioned
Timezone / hours
Not specified
Citizenship requirement
Not mentioned
Work authorization
Not specified

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READ IT IN THE EMPLOYER’S OWN WORDS

Original job description

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About Sygaldry Sygaldry Technologies is building quantum-accelerated AI servers to exponentially speed up training and inference for AI. By integrating quantum and AI, we're accelerating the path to super intelligence, and engineering the conditions for it to scale efficiently and operate affordably. Sygaldry AI servers combine multiple qubit types within a single, fault-tolerant architecture to deliver the combination of cost, scale, and speed necessary for advanced AI applications. We pioneer new domains in physics, engineering, and AI, tackling the hardest challenges with a grounded, optimistic, and rigorous culture. We're looking for individuals ready to define the intersection of quantum and AI and drive its profound global impact. What You’ll Work On
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This role is focused on the modeling and simulation of high-performing AI hardware, and does not require prior knowledge of quantum computers. It will interface with a variety of internal teams and external partners with whom we are planning to collaborate. We will share more detail about this role during in-person discussions. Key responsibilities: Develop performance models and simulators for large-scale distributed ML systems and emerging AI acceleration platforms. Model end-to-end training and inference performance across compute, memory, networking, and communication. Analyze workload parallelism, collective communication, scheduling, and data movement to identify system-level bottlenecks. Explore system architectures and hardware/software tradeoffs to improve performance, scalability, and efficiency. Build simulation frameworks for rapid design-space exploration across distributed GPU and next-generation accelerator systems. Collaborate with ML researchers, compiler engineers, and system architects to guide next-generation AI system design. You May Be a Fit if You Have: PhD in Computer Engineering or Electrical Engineering with 2-5 years relevant work experience A strong research track record, including publications at top-tier venues such as ISCA, MICRO, ASPLOS, MLSys, SOSP, VLDB, OSDI, or other leading systems conferences. Strong foundations in ML systems, distributed computing, and performance modeling. Experience with large-scale ML training or inference systems and distributed execution frameworks. Understanding of model parallelism, data parallelism, collective communication, and distributed scheduling. Experience building simulators, analytical performance models, or system-level benchmarking tools. Familiarity with GPU clusters, high-performance networking, and AI accelerator systems. Ability to reason from first principles, identify bottlenecks, and independently tackle open-ended research problems. Passion for rethinking how next-generation AI systems are designed and scaled. How We’re Different At Sygaldry, curiosity and intellectual courage drive our work. We approach ambitious challenges with a grounded, optimistic, and rigorous culture and know that kind people build the strongest teams. We prioritize mission over ego and collaborate openly with a strong sense of shared purpose. We dream big, yet we execute with a love of detail. We’re looking for scientists, engineers, and operators to forge new paths with us at the intersection of quantum and AI. Culture & Benefits Visa Sponsorship - We know what it takes to make top talent thrive here. We’re open to supporting visas whenever possible. Compensation - We value your contribution and invest in your future with a competitive salary and meaningful equity. Benefits - Your well-being matters. We provide company-sponsored health coverage to give you and your family peace of mind. Connection - Whether it’s company offsite or casual crew socials, we make time to connect, recharge, and have fun together. Time Off - We trust you to take the time you need. Unlimited PTO so you can rest, recharge, and come back ready to make an impact. We encourage applications from candidates with diverse backgrounds. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. We encourage you to apply even if you do not believe you meet every single qualification. If you don’t think this role is right for you, but you believe that you would have something meaningful to contribute to our mission, please reach out at letsbuild@sygaldry.com. Location: This position can be located on-site in San Francisco, CA or Ann Arbor, MI
Original formatting and links

About Sygaldry

Sygaldry Technologies is building quantum-accelerated AI servers to exponentially speed up training and inference for AI. By integrating quantum and AI, we're accelerating the path to super intelligence, and engineering the conditions for it to scale efficiently and operate affordably. Sygaldry AI servers combine multiple qubit types within a single, fault-tolerant architecture to deliver the combination of cost, scale, and speed necessary for advanced AI applications. We pioneer new domains in physics, engineering, and AI, tackling the hardest challenges with a grounded, optimistic, and rigorous culture. We're looking for individuals ready to define the intersection of quantum and AI and drive its profound global impact.

What You’ll Work On

This role is focused on the modeling and simulation of high-performing AI hardware, and does not require prior knowledge of quantum computers. It will interface with a variety of internal teams and external partners with whom we are planning to collaborate. We will share more detail about this role during in-person discussions.

Key responsibilities:

  • Develop performance models and simulators for large-scale distributed ML systems and emerging AI acceleration platforms.

  • Model end-to-end training and inference performance across compute, memory, networking, and communication.

  • Analyze workload parallelism, collective communication, scheduling, and data movement to identify system-level bottlenecks.

  • Explore system architectures and hardware/software tradeoffs to improve performance, scalability, and efficiency.

  • Build simulation frameworks for rapid design-space exploration across distributed GPU and next-generation accelerator systems.

  • Collaborate with ML researchers, compiler engineers, and system architects to guide next-generation AI system design.

You May Be a Fit if You Have:

  • PhD in Computer Engineering or Electrical Engineering with 2-5 years relevant work experience

  • A strong research track record, including publications at top-tier venues such as ISCA, MICRO, ASPLOS, MLSys, SOSP, VLDB, OSDI, or other leading systems conferences.

  • Strong foundations in ML systems, distributed computing, and performance modeling.

  • Experience with large-scale ML training or inference systems and distributed execution frameworks.

  • Understanding of model parallelism, data parallelism, collective communication, and distributed scheduling.

  • Experience building simulators, analytical performance models, or system-level benchmarking tools.

  • Familiarity with GPU clusters, high-performance networking, and AI accelerator systems.

  • Ability to reason from first principles, identify bottlenecks, and independently tackle open-ended research problems.

  • Passion for rethinking how next-generation AI systems are designed and scaled.

How We’re Different

At Sygaldry, curiosity and intellectual courage drive our work. We approach ambitious challenges with a grounded, optimistic, and rigorous culture and know that kind people build the strongest teams. We prioritize mission over ego and collaborate openly with a strong sense of shared purpose. We dream big, yet we execute with a love of detail. We’re looking for scientists, engineers, and operators to forge new paths with us at the intersection of quantum and AI.

Culture & Benefits

  • Visa Sponsorship - We know what it takes to make top talent thrive here. We’re open to supporting visas whenever possible.

  • Compensation - We value your contribution and invest in your future with a competitive salary and meaningful equity.

  • Benefits - Your well-being matters. We provide company-sponsored health coverage to give you and your family peace of mind.

  • Connection - Whether it’s company offsite or casual crew socials, we make time to connect, recharge, and have fun together.

  • Time Off - We trust you to take the time you need. Unlimited PTO so you can rest, recharge, and come back ready to make an impact.

We encourage applications from candidates with diverse backgrounds. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.

We encourage you to apply even if you do not believe you meet every single qualification. If you don’t think this role is right for you, but you believe that you would have something meaningful to contribute to our mission, please reach out at letsbuild@sygaldry.com.

Location: This position can be located on-site in San Francisco, CA or Ann Arbor, MI

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