S

Sygaldry Technologies

Provides quantum-accelerated AI server infrastructure

Research Scientist - Frontier AI/ML & Quantum Algorithms

Full-Time
$200k - $300k/yr+ Equity
Mid
San Francisco, CA, USA
In Person
AI & Machine LearningAI Research
H1B Sponsorship Available

About the job

Requirements
  • Have a research record in machine learning, artificial intelligence, statistics, physics, applied mathematics, computer science, quantum information, or a related field.
  • Have deep expertise in at least two of generative modeling, probabilistic inference, uncertainty quantification, geometric deep learning, graph neural networks, optimization, reinforcement learning or control, numerical methods, scientific machine learning, quantum algorithms, or quantum information.
  • Have published research relevant to audiences at NeurIPS, ICML, ICLR, AISTATS, UAI, COLT, QIP, TQC, PRX Quantum, Nature, Science, or similar venues.
  • Be able to derive algorithms, build prototypes, run careful experiments, and communicate results clearly.
  • Have experience with machine learning frameworks such as PyTorch or JAX and efficient inference implementation.
  • Be excited to work with quantum hardware teams and help define AI workloads for future fault-tolerant quantum systems.
  • Communicate complex ideas clearly across research communities.
  • Be comfortable assessing where quantum computation can help, where it cannot, and what evidence would distinguish the two.
Responsibilities
  • Develop and study models for high-dimensional scientific prediction, generation, and design, including diffusion models, flow matching, consistency models, score-based generative models, energy-based models, latent-variable models, autoregressive models, and normalizing flows.
  • Develop scientific foundation models for molecules, materials, proteins, quantum systems, weather, climate, partial differential equations, and dynamical systems.
  • Develop graph neural networks, geometric deep learning, equivariant models, neural operators, tensor methods, manifold learning, and learning on structured state spaces.
  • Build models that combine prediction, uncertainty, active learning, and closed-loop design for scientific discovery.
  • Build algorithms and theory for probabilistic inference, Bayesian modeling, variational inference, Monte Carlo methods, simulation-based inference, uncertainty quantification, and calibration.
  • Build algorithms and theory for optimization, sampling, amortized inference, sequential decision-making, Bayesian experimental design, reinforcement learning, planning, and control.
  • Develop scientific reasoning systems, model-guided discovery, algorithmic discovery, and agents that can propose, test, and refine hypotheses.
  • Develop benchmarking frameworks to reveal when a new computational substrate changes scaling behavior rather than only constant factors.
  • Identify where quantum computation can accelerate or reshape AI-relevant subroutines, including sampling, integration, Monte Carlo acceleration, linear algebra, optimization, Hamiltonian simulation, quantum simulation, and tensor-structured computation.
  • Develop or assess fault-tolerant quantum algorithms, resource estimation, complexity analysis, block encoding, QSVT, LCU methods, amplitude estimation, phase estimation, and quantum walks.
  • Develop hybrid quantum-classical workflows that embed quantum primitives inside classical AI pipelines.
  • Develop mathematically motivated quantum-native model classes, kernels, embeddings, generative processes, and inference procedures.
  • Translate AI and scientific-computing bottlenecks into quantum resource requirements.
  • Design benchmarks that compare quantum, classical, and hybrid approaches under realistic assumptions.
  • Inform architecture choices by identifying the algorithms, error budgets, and primitives that matter for future AI workloads.
  • Build prototypes in Python, JAX, or PyTorch and, when useful, use quantum software frameworks such as PennyLane, Qiskit, Cirq, CUDA-Q, TensorCircuit, or custom simulators.
  • Collaborate with quantum architecture, systems, and hardware teams to connect AI workloads to real machine requirements.
Desired Qualifications
  • Research experience in diffusion or flow models, energy-based models, probabilistic programming, Bayesian deep learning, neural stochastic or ordinary differential equations, simulation-based inference, or scalable Monte Carlo.
  • Experience with AI for science, including molecular design, protein design, drug discovery, materials discovery, weather or climate prediction, quantum chemistry, partial differential equation modeling, dynamical systems, robotics, or control.
  • Experience with graph or geometric learning, equivariant architectures, neural operators, tensor networks, manifold methods, or structured world models.
  • Background in quantum algorithms, computational complexity, quantum simulation, quantum chemistry, fault tolerance, resource estimation, or quantum information theory.
  • Experience with JAX, PyTorch, CUDA or Triton, distributed training or inference, differentiable simulation, or high-performance scientific computing.
  • A track record of publishing, open-source software, or building research systems that influenced a field.

About the company

S

Sygaldry Technologies

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Sygaldry Technologies builds quantum-accelerated AI servers and the infrastructure to run advanced AI models. It pairs quantum capabilities with AI workflows using a fault-tolerant architecture that combines several qubit modalities to speed up training and inference. It differentiates itself by integrating multiple qubit technologies within a single scalable platform rather than relying on one quantum approach. Its goal is to deliver affordable, sustainable, personalized, and secure superintelligence through practical quantum AI servers.

Company Size

11-50

Company Stage

Series A

Total Funding

$139.1M

Headquarters

Ann Arbor, Michigan

Founded

2024

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Simplify's Take

What believers are saying

  • Sygaldry raised $139 million in 2026 from Breakthrough Energy Ventures and Initialized Capital.
  • The company posted eleven open roles in July 2026, signaling active product and team buildout.
  • Breakthrough Energy backs Sygaldry to attack AI data-center power growth and unsustainable model energy costs.

What critics are saying

  • Sygaldry has no customer revenue, and commercialization slips beyond 2030 burn investor patience.
  • NVIDIA NVQLink and Rigetti's 2026 hardware progress commoditize Sygaldry's hybrid infrastructure thesis.
  • If quantum-accelerated AI proves uneconomic, Sygaldry becomes a science project before market validation.

What makes Sygaldry Technologies unique

  • Chad Rigetti, Idalia Friedson, and Michael Keiser founded Sygaldry in 2024.
  • Sygaldry targets AI data centers with quantum hardware plus classical chips, not standalone quantum computers.
  • Its Ann Arbor HQ and San Francisco office anchor recruiting near Michigan and Bay Area talent.

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Benefits

  • Health Insurance
  • Unlimited Paid Time Off
  • Company Equity

Growth & Insights and Company News

Headcount

6 month growth

0%

1 year growth

37%

2 year growth

5%
Ann Arbor Times
Sep 4th, 2026
Quantum computing company Sygaldry Technologies establishes headquarters in Ann Arbor.

Quantum computing company Sygaldry Technologies establishes headquarters in Ann Arbor. Sygaldry Technologies, a quantum computing company building servers for artificial intelligence, has established its headquarters in Ann Arbor and a second office in San Francisco, according to a Sep. 4 article by Erin Gregory of Purpose Jobs. The company is developing advanced computing hardware aimed at making AI more efficient and sustainable. In April 2026, Sygaldry announced it had raised $139 million to build quantum-powered AI servers, including a $105 million Series A led by Breakthrough Energy Ventures and a $34 million seed round led by Initialized Capital. Idalia Friedson, co-founder of Sygaldry Technologies, said the company's goal is to use quantum technology to address the high cost and energy consumption associated with training large AI models. "We want to make AI more affordable, more sustainable than it otherwise would be without quantum computing," Friedson said. Friedson described Sygaldry as focused entirely on using quantum computing to improve artificial intelligence. "We're arguably the only company that's 100% focused on how you can improve AI with quantum," she said. The University of Michigan has been recognized as a national leader in AI research; in 2025, the Brookings Institution named Ann Arbor one of 28 'Star Hubs' for AI readiness and identified it as part of the country's second engine of AI development. Additionally, the university is partnering with Los Alamos National Laboratory on an advanced research facility in Washtenaw County. Other companies such as Rydberg Technologies and MONSTR Sense Technologies are also active in the region's quantum technology sector but do not focus specifically on applying quantum computing to artificial intelligence like Sygaldry does. Friedson emphasized that combining expertise from both fields strengthens local innovation efforts. Friedson credited Ann Arbor SPARK for supporting Sygaldry's move and helping recruit talent: "They've just been an amazing resource from day one." She noted that while talent often gravitates toward expensive cities known for tech innovation, building operations in Ann Arbor allows employees access to frontier technology work along with improved quality of life and lower living costs compared to those cities. Looking ahead, Friedson sees an opportunity for Michigan to become recognized as a leader at the intersection of quantum computing and artificial intelligence if investment continues into talent development and infrastructure. With its recent funding round, Sygaldry plans further hiring across both locations.

Ann Arbor SPARK
Sep 4th, 2026
A quantum company building servers for AI chose Ann Arbor.

A quantum company building servers for AI chose Ann Arbor. By erin gregory, purpose jobs. On the first floor of Domino's Farms, the office complex north of Ann Arbor, sits a quantum computing lab. Out back, there's a herd of bison. Idalia Friedson, a co-founder of Sygaldry Technologies, smiles when she describes the setup. Her company is building some of the most advanced computing hardware in the country from its Ann Arbor headquarters and its second office in San Francisco. In April 2026, Sygaldry announced it had raised $139 million to build quantum-powered AI servers: a $105 million Series A led by Breakthrough Energy Ventures, on top of a $34 million seed round led by Initialized Capital. Michigan has spent the past few years making a case for itself as a serious place to do AI work, so this fundraise is a sign of progress. A growing group of companies and researchers here are working at the intersection of quantum computing and AI. Why quantum and AI are coming together. Friedson has worked in and around quantum computing for about a decade. The technology uses the rules of physics at the atomic scale to solve problems ordinary computers can't. She started in technology and national security policy at a Washington, D.C think tank, where she helped launch the world's first quantum policy center, then moved into the tech industry as a product manager before joining Chad Rigetti's first company, Rigetti Computing, where she helped take the business public. Rigetti, who founded and led that company before leaving in 2022, is now Sygaldry's CEO and one of its three co-founders, along with Friedson and AI scientist Michael Keiser. What drew Friedson to quantum computing is what it can do that nothing else can. "When I learned about quantum computing, I thought this is almost unbelievable, the type of impact it could potentially make," she said. Quantum machines can take on problems that ordinary computers cannot practically solve. Some would take "more than the lifetime of the universe to solve on the current computers that we have," she said. Sygaldry is aiming that capability at one problem in particular: the cost and energy of running AI. Training and operating large AI models takes enormous amounts of power, and the strain on data centers and the electric grid has become one of the industry's biggest limits on growth. Sygaldry's servers are designed to work as a co-processor inside the data center, running next to the classical GPUs that AI companies already use. The goal, Friedson said, is to get more computing out of each watt of energy going in. "We want to make AI more affordable, more sustainable than it otherwise would be without quantum computing," she said. The company building the bridge in Ann Arbor. Sygaldry describes itself as focused entirely on one question: how to use quantum computing to make AI better. "We're arguably the only company that's 100% focused on how you can improve AI with quantum," Friedson said. She sees Sygaldry as a bridge between these two communities that have been growing in the region somewhat separately. On the AI side, the University of Michigan is a national leader in AI research. In 2025, the Brookings Institution named Ann Arbor one of 28 "Star Hubs" in its report on AI readiness, and a group it described as the country's second engine of AI development. The university and the Los Alamos National Laboratory in New Mexico are also developing a high-performance computing and AI research facility in Washtenaw County, part of a partnership the two institutions announced in late 2024. Neither Rydberg Technologies nor MONSTR Sense Technologies builds quantum computing for AI the way Sygaldry does, but both show the region already has meaningful work underway in quantum technology and advanced measurement, alongside the university's own quantum research institute. Rydberg Technologies, founded in Ann Arbor in 2015, builds quantum sensors that measure radio-frequency signals with a precision ordinary antennas cannot reach, and has demonstrated long-range radio communication using an atomic sensor at a U.S. Army testing event. MONSTR Sense Technologies, a University of Michigan spinout, makes ultrafast imaging instruments that researchers and semiconductor manufacturers use to analyze materials and find defects on silicon wafers. Friedson's point is that these two threads, AI and quantum, are stronger together, and that a company working on both at once can help connect them. Building a company with Michigan roots. Michigan's universities produce strong engineers and scientists. Keeping them here is the harder problem, and it's the one Friedson returns to most. Building a deep-tech company takes more than good science. It takes turning research into a business that can grow and wants to stay in the state, which means holding onto the people who can build it. That is where she credits Ann Arbor SPARK. "They've just been an amazing resource from day one," Friedson said. SPARK has helped Sygaldry recruit and promote open roles, and it has worked with employees the company relocated to Ann Arbor to get them settled, including connecting their spouses and partners to job opportunities. SPARK has supported Sygaldry since its move to Ann Arbor, assisting with talent recruitment and industry connections. Quantum and AI talent tends to concentrate in a few expensive cities. Building in Ann Arbor, Friedson said, lets the company work on frontier technology while offering employees a quality of life and a cost of living that those cities cannot match. Keeping the San Francisco office gives Sygaldry a foot in both worlds. What Michigan could become. Friedson thinks the state has a specific opening. "There's an opportunity for Michigan to put itself on the map as the leader at the intersection of quantum and AI," she said. Getting there, in her view, takes continued investment in talent and in the infrastructure to support it, along with policies that back quantum and AI work. It also takes organizations like SPARK that make it easier for startups to form and grow. For now, Sygaldry is hiring. The $139 million is going toward building out its quantum and AI teams across Ann Arbor and San Francisco, with open roles in quantum engineering, AI research, go-to-market, and product. Friedson believes AI and quantum will shape the next era of computing together, and she wants Michigan to be where that combination gets built. Sygaldry's raise is the strongest evidence so far for that argument. Whether more companies and investment follow will show whether it holds up.

Latitude Media
May 11th, 2026
Can quantum computing help solve the load growth problem?

Can quantum computing help solve the load growth problem? A new Breakthrough Energy investment in quantum comes as the technology increasingly falls under the climate tech umbrella. May 11, 2026 When Breakthrough Energy Ventures announced a new investment in quantum computing last month, it raised some eyebrows. Did the addition really fit into the firm's focus on clean energy and climate tech, certain observers wonder, or might it be stretching the definition a bit? Breakthrough led the $105 million Series A funding round of Sygaldry Technologies, a startup building quantum computers with the goal of making artificial intelligence models faster and more efficient. Other investors included Y Combinator, Initialized Capital, Rock Yard Ventures, and Earth Venture Capital; the last is the only other one with a decarbonization mandate driving its investments. Sygaldry isn't the first time Breakthrough Energy invests in quantum computing. In 2021, the firm participated in the $350 million private investment in public equity (or PIPE) funding round for IonQ, a hardware and software quantum computing developer. But this latest commitment, coming at a time when rapidly increasing load growth from data centers and AI is threatening the reliability of energy systems across the world, is putting a spotlight on quantum computing's energy-saving potential. In an emailed statement to Latitude Media, Carmichael Roberts, managing partner at Breakthrough Energy, said that part of the rationale behind the investment comes from the fact that large language models' energy intensity is becoming unsustainable. "We believe new computing platforms such as quantum computing have the potential to break this paradigm," he wrote. Traditional computing relies on classical physics to process information via a binary code system made of ones and zeroes. Quantum computing, however, relies instead on quantum mechanics, using units called "qubits," which "can exist in multiple states at the same time" through "quantum states," per Microsoft's definition: "This structure allows teams to explore complex problems in new ways, especially when traditional approaches are too slow or impractical." The technology for decades was used primarily in university and research lab context. But as it gains more widespread momentum, part of quantum computing's promise is a superior processing power that also makes it more energy efficient. As Mark Cupta, managing director at Prelude Ventures, notes, that's a key reason why quantum computing has long been considered by investors, including Breakthrough Energy and Prelude itself, a climate investment. "The beauty of a quantum computer is that it will be up to many orders of magnitude more energy efficient," Cupta said. "There are some problems that a quantum computer can solve that all the computers on Earth could not accomplish in any relevant human timescale. In those cases, you've got an effectively incalculable energy savings." Prelude has been invested in quantum computing since 2018, when it first backed the then-brand-new Atom Computing, a hardware platform developing large-scale quantum computers. At the time, Cupta, who led the investment, was already concerned about how energy demand from data center computing was starting to outpace normal load growth. "AI has lit multiple fires underneath that theme," Cupta said. "And that's because of the energy intensity of the brute force mathematical methodology used in today's AI models." That urgency comes as quantum technology is reaching what an April 2026 report by McKinsey calls a "commercial tipping point." According to the report, over 300 companies globally have started adopting some level of quantum computing, and investors have been paying more attention, with investment in quantum technology startups reaching $12.6 billion in 2025, more than six times higher than the previous year. Beyond energy efficiency. Of course, quantum is attractive to a wide range of investors, often with deeper pockets than those specializing in climate tech. But for those climate investors choosing to put money in the technology, the reasoning can go beyond its potential energy savings. For one, the fact that quantum computers can potentially explore a large number of possibilities at once, rather than testing every solution to a problem one by one, can help with complex optimization challenges, such as how to best operate the grid or a supply chain. And because quantum essentially behaves like the molecules in nature, it's uniquely suited to simulate the physical world and find the best materials for a variety of applications. "We would be able to find the most ideal carbon capture substrate, or the catalyst that uses the least amount of energy to make chemicals like fertilizer, or simulate and discover world-changing materials like a room temperature superconductor," Cupta said, adding that a "significant amount of what we invest in could benefit from the existence of a quantum computer to help accelerate speed to market." These are what Morgan Sheil, chief climate officer at the World Fund, a European climate-focused VC investor, calls the "indirect" climate impacts of quantum computing, beyond its energy efficiency benefits. "There's a massive number of use cases that can be unlocked by compute in terms of reducing emissions and optimizing, given that there are a lot of systems that are not particularly optimized or particularly smart," she said. The World Fund has been investing in quantum computing since 2022, when it led the 128 million-euro (roughly $133 million at the time) Series A funding round for IQM Quantum Computers, a European hardware and software platform. At the time, the World Fund was investing in technologies with the potential to reduce emissions by 100 megatons per year by 2040, and part of the IQM assessment was how impactful its technology could be for batteries and energy storage. From solar and storage to data centers: 7 trends in power infrastructure for 2026. Learn about the forces impacting power infrastructure development, and what it will take to build and scale future projects. Per the assessment, the startup's technology could not only help better integrate storage systems into the grid, but also help replace lithium-ion batteries with lithium-sulfur batteries, lowering costs, encouraging adoption, and improving batteries' energy density. (In 2024, IQM announced it was collaborating with German automaker Volkswagen to use quantum computing to simulate battery chemistry and look for a more efficient battery design.) "Even if it impacted 1% to 5% of the total emissions in a battery market, that would be significant," she said. Of course, like many of the new technologies climate tech funds invest in, quantum computing is not commercially available at scale yet, and its potential to impact even a small slice of the market by 2040 remains to be seen. But Sheil is optimistic, and has a growing body of research to back up that enthusiasm. According to McKinsey, 72% of quantum computing use is now by companies in the private sector, a suggestion that the technology is stretching beyond the province of universities and research labs and starting to reach a broader market. * Bianca Giacobone Bianca Giacobone is a contributing reporter at Latitude Media. She is a freelance business reporter and fact-checker covering the clean energy transition, based in Italy. Related Reading Stay ahead of energy's next frontier. Subscribe for free:

GlobeNewswire
Apr 14th, 2026
Sygaldry raises $139M to build quantum computers for AI

Sygaldry raises $139M to build quantum-accelerated AI infrastructure for faster, more energy-efficient data center computing...

Microsoft
Apr 14th, 2026
Chad Rigetti's Sygaldry raises $139M to bring quantum hardware to AI data centers

Chad Rigetti's quantum computing startup Sygaldry has raised $139 million to develop quantum hardware for AI data centres. The funding includes a $105 million Series A led by Breakthrough Energy Ventures and a $34 million seed round led by Initialized Capital. Founded in 2024 by Rigetti, Idalia Friedson and Michael Keiser, Sygaldry is designing servers that combine quantum hardware with classical chips to run AI workloads faster than Nvidia GPUs. Rigetti, who previously founded Rigetti Computing in 2013, aims to have commercial quantum machines providing speed improvements for AI workloads by the end of the decade. Investors believe the approach addresses AI's growing energy consumption problem, with Breakthrough Energy Ventures citing the unsustainable energy intensity of large language models.