Quantum Machine Learning Engineer information
See Chandler, AZ salary details
$30.9K - $45.4K
1% of jobs
$45.4K - $59.9K
1% of jobs
$59.9K - $74.3K
5% of jobs
$74.3K - $88.8K
6% of jobs
$100.7K is the 25th percentile. Wages below this are outliers.
$88.8K - $103.2K
14% of jobs
$103.2K - $117.7K
14% of jobs
The median wage is $124.9K / yr.
$117.7K - $132.2K
18% of jobs
$132.2K - $146.6K
14% of jobs
$149.6K is the 75th percentile. Wages above this are outliers.
$146.6K - $161.1K
12% of jobs
$161.1K - $175.6K
11% of jobs
$175.6K - $190K
5% of jobs
How much do quantum machine learning engineer jobs pay per year?
As of Aug 14, 2026, the average yearly pay for quantum machine learning engineer in Chandler, AZ is $126,456.00, according to ZipRecruiter salary data. Most workers in this role earn between $99,700.00 and $152,200.00 per year, depending on experience, location, and employer.
A Quantum Machine Learning Engineer is a professional who combines expertise in quantum computing and machine learning to develop algorithms and solutions that leverage quantum hardware for advanced data processing tasks. They work on designing, implementing, and testing quantum algorithms that can solve problems faster or more efficiently than classical computers. Their work often involves collaborating with physicists, data scientists, and software engineers to bridge the gap between quantum theory and practical applications. This role requires strong backgrounds in quantum mechanics, computer science, and statistical learning techniques.
Quantum Machine Learning Engineers often serve as a bridge between classical machine learning experts and quantum hardware specialists. They work closely with data scientists to adapt machine learning algorithms for quantum environments and collaborate with hardware teams to ensure algorithms are optimized for specific quantum processors. Regular cross-functional meetings, code reviews, and joint problem-solving sessions are common, fostering a highly collaborative work environment. This collaboration is essential for successfully integrating quantum solutions into existing workflows and advancing the organization's quantum computing initiatives.
To thrive as a Quantum Machine Learning Engineer, you need a strong background in quantum computing, machine learning, linear algebra, and programming (often Python or C++), typically supported by an advanced degree in physics, computer science, or a related field. Familiarity with platforms like Qiskit, Cirq, or TensorFlow Quantum, and knowledge of quantum algorithms and cloud-based quantum computing services are essential. Creative problem-solving, analytical thinking, and strong collaboration skills help distinguish top performers in this interdisciplinary field. Mastery of these skills enables innovation in developing and deploying quantum machine learning solutions to solve complex, cutting-edge problems.
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