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Quantum Machine Learning Jobs in California (NOW HIRING)

Qualcomm

Machine Learning Researcher

San Diego, CA · On-site

... quantum machine learning). • Develops and publishes research findings in the form of presentations and conference papers. • Conducts research on machine learning and develops innovative or ...

Visa

Staff Research Scientist

Foster City, CA · On-site

$169K/yr

The ideal candidate will focus on conducting advanced research in one or more subfields, for example, quantum error correction, quantum optimization, quantum simulation, quantum machine learning ...

LLNL

Machine Learning Physics Graduate Student

Livermore, CA · On-site

$6.7K - $8.2K/mo

... quantum simulations. * Explore the use of machine learning methods to discover and evolve PDEs for ... phase field and phase field crystal models. * Analyze results, provide weekly updates and present ...

Amazon

Machinist, Quantum Computing

Pasadena, CA · On-site

$23.75 - $32.50/hr

In this role, you will support the CNC machine shop with parts production and day-to-day shop ... The ideal candidate demonstrates a strong commitment to continuous learning and professional growth ...

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All JobsQuantum Machine Learning JobsQuantum Machine Learning Jobs in California

Quantum Machine Learning information

See California salary details

$25.2K

$42K

$86.8K

How much do quantum machine learning jobs pay per year?

As of Jul 27, 2026, the average yearly pay for quantum machine learning in California is $42,026.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,100.00 and $45,400.00 per year, depending on experience, location, and employer.

Is quantum machine learning a good career?

Quantum machine learning is an emerging field combining quantum computing and machine learning, with growing research and industry interest. Careers in this area typically require strong backgrounds in quantum physics, computer science, and programming skills, often involving specialized tools like quantum algorithms and hardware. As the field develops, demand for experts is expected to increase, making it a promising career path for those with relevant expertise.

Which 3 jobs will survive AI?

Quantum machine learning professionals, data scientists, and software engineers are likely to continue thriving as AI advances, due to their specialized skills in developing, understanding, and managing complex algorithms and quantum computing tools. These roles require critical thinking, domain expertise, and adaptability to evolving technologies, making them less susceptible to automation. Continuous learning and certification in AI and quantum technologies can further enhance job security in these fields.

What are the key skills and qualifications needed to thrive in the Quantum Machine Learning position, and why are they important?

To thrive in Quantum Machine Learning, you need a solid background in quantum physics, machine learning, linear algebra, and programming—often supported by a graduate degree in a related field. Familiarity with quantum computing frameworks such as Qiskit or Cirq, and experience with conventional ML libraries like TensorFlow or PyTorch are typically expected. Strong problem-solving abilities, effective communication, and a collaborative mindset help professionals stand out. Mastery of these skills and qualities is essential for tackling complex interdisciplinary challenges and driving innovation in this rapidly evolving field.

What types of projects or problems does a Quantum Machine Learning professional typically work on?

Quantum Machine Learning professionals often work on exploratory projects at the intersection of quantum computing and artificial intelligence, such as developing new algorithms that leverage quantum hardware for faster data processing or optimizing classical ML models using quantum techniques. Daily tasks may include designing experiments, simulating quantum systems, analyzing results, and collaborating with physicists and software engineers. The work can range from foundational research to applied development, depending on the organization's focus. These roles frequently involve teamwork and staying updated on emerging academic and industry advances to ensure innovative problem-solving approaches.

What is the salary of quantum machine learning?

Salaries for quantum machine learning professionals vary based on experience, education, and location, but typically range from $80,000 to over $150,000 annually. Entry-level roles may start lower, while experienced researchers or specialists with advanced skills in quantum computing and machine learning can earn higher salaries. Many positions also offer benefits such as research funding and access to cutting-edge technology.

What is a Quantum Machine Learning job?

A Quantum Machine Learning (QML) job involves applying principles of quantum computing to machine learning tasks. Professionals in this field develop algorithms that leverage quantum systems to improve computational efficiency and solve complex problems faster than classical methods. Responsibilities often include researching quantum algorithms, implementing quantum circuits, and working with tools like Qiskit or TensorFlow Quantum. These roles are typically found in research labs, tech companies, and startups exploring the intersection of AI and quantum technology. Strong backgrounds in quantum mechanics, linear algebra, and computer science are essential.

Is Q-Ctrl a real company?

Q-Ctrl is a real company that specializes in quantum control solutions and software for quantum computing. It provides tools and expertise to help improve qubit performance and error correction in quantum systems, which can be relevant for professionals in quantum machine learning roles.
What are popular job titles related to Quantum Machine Learning jobs in California? For Quantum Machine Learning jobs in California, the most frequently searched job titles are:
What job categories do people searching Quantum Machine Learning jobs in California look for? The top searched job categories for Quantum Machine Learning jobs in California are:
What cities in California are hiring for Quantum Machine Learning jobs? Cities in California with the most Quantum Machine Learning job openings:
Quantum Machine Learning jobs near you
Infographic showing various Quantum Machine Learning job openings in California as of July 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $42,026 per year, or $20.2 per hour.

Machine Learning Engineer

Quantum Machines

Santa Barbara, CA • On-site

Full-time

Posted 28 days ago

Job description

Description
Quantum Machines (QM) is a global leader in quantum computing control systems. Through our pioneering hardware and software solutions based on instruction-based quantum control, we're revolutionizing how quantum computers are built and controlled. As we stand at the forefront of exponential growth in quantum computing, we're assembling an elite team that actively shapes the evolution of quantum technologies.
We are looking for a Machine Learning Engineer to design, build, and deploy machine learning systems that improve the calibration, control, and operation of quantum processors. In this role, you will work at the intersection of machine learning, quantum physics, and software engineering, translating noisy, non-stationary, safety-critical control problems into ML solutions that run on real hardware in production labs.
You will develop reinforcement learning policies, Bayesian inference methods, and agentic frameworks that make quantum control more autonomous, more sample-efficient, and more robust to drift. This position offers unprecedented exposure to diverse qubit types and quantum architectures, with a tight feedback loop between your models and the systems they steer, and the opportunity to deliver groundbreaking ML-driven solutions to the labs and companies defining the next generation of quantum systems.
Responsibilities:
  • Develop reinforcement learning, Bayesian inference, and probabilistic modelling approaches for parameter tuning, drift tracking, and adaptive measurement, to be deployed on real hardware.
  • Develop real-time parameter steering for calibration during QEC and between circuits.
  • Develop and maintain agentic frameworks for autonomous system control and calibration.
  • Develop and maintain Python-based ML services and libraries that integrate with the wider Quantum Machines control stack, including QUA, Qualibrate, and the OPX1000.
  • Work directly with customers and partner labs to deploy, validate, and iterate on ML solutions in real experimental environments.
  • Collaborate cross-functionally with product, R&D, and hardware teams, contributing to internal libraries, customer-facing SDKs, and training materials.

Requirements
  • PhD/Master in Machine Learning, Physics, Applied Physics, Quantum Information Science, or a related field. 4+ years of relevant experience
  • Strong background in Machine Learning and Deep Learning, with hands-on experience in at least one of: deep learning, reinforcement learning, agentic AI
  • Strong Python proficiency, including scientific or systems-oriented codebases
  • Solid software engineering fundamentals (architecture, Git workflows, testing, code review)
  • Proven track record of taking ML from prototype to deployment under real-world constraints - non-stationary data, expensive evaluations, or safety-critical action spaces. Robotics, online control, autonomous vehicles, or hardware-in-the-loop ML all transfer well
  • Strong problem-solving skills and customer-focused mindset; ability to work independently and in multidisciplinary teams
  • Proven software development track record and excellent technical communication skills
  • Familiarity with quantum computing concepts - qubit calibration, randomized benchmarking, QEC, optimal control- advantage
  • Experience with sim-to-real, multi-objective RL, or meta-learning- advantage

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