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Quantum Machine Learning Engineer Jobs in Fontana, CA

Esri

C/C++ Software Development Engineer II

Redlands, CA · On-site

Work alongside senior engineers to design and implement innovative features * Stay informed about ... machine learning, computer hardware, and the business of software, to enhance your contributions to ...

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Quantum Machine Learning Engineer information

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$32K

$130.9K

$196.7K

How much do quantum machine learning engineer jobs pay per year?

As of Aug 28, 2026, the average yearly pay for quantum machine learning engineer in Fontana, CA is $130,912.00, according to ZipRecruiter salary data. Most workers in this role earn between $103,200.00 and $157,600.00 per year, depending on experience, location, and employer.

What is a quantum machine learning engineer?

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.

What are the key skills and qualifications needed to thrive as a quantum machine learning engineer?

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.

How do quantum machine learning engineers typically collaborate with classical machine learning teams and quantum hardware specialists?

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.

Is quantum machine learning a good career?

Quantum machine learning engineers work at the intersection of quantum computing and machine learning, focusing on developing algorithms that leverage quantum hardware. The field is emerging with high growth potential, requiring skills in quantum algorithms, programming languages like Python, and understanding of both quantum mechanics and machine learning principles. As quantum technology advances, demand for specialists in this area is expected to increase, making it a promising career path for those with relevant expertise.

What job categories do people searching Quantum Machine Learning Engineer jobs in Fontana, CA look for?

The top searched job categories for Quantum Machine Learning Engineer jobs in Fontana, CA are:

What cities near Fontana, CA are hiring for Quantum Machine Learning Engineer jobs?

Cities near Fontana, CA with the most Quantum Machine Learning Engineer job openings:

Quantum Machine Learning Engineer jobs near you

Staff Machine Learning Engineer (Mountain View)

Victorville, CA • On-site

Intuit Inc.
Computer and Electronic Product Manufacturing • 5 - 10K employees

8.2

Company rating: 8.2 out of 10

Based on 92 frontline employees who took The Breakroom Quiz

107th of 246 rated software companies

People enjoy working here

Good employer

Recommended by students

Learn more about Intuit Inc.external

$197K - $266K/yr

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

Overview

Come join Intuit as a Staff Machine Learning Engineer!

In this role, you’ll be embedded inside a vibrant team of data scientists. You’ll be expected to help conceive, code, and deploy data science models at scale using the latest industry tools. Important skills include data wrangling, feature engineering, developing models, and testing metrics.

Responsibilities
  • Discover data sources, get access to them, import them, clean them up, and make them “machine learning ready”.
  • Work with data scientists to create and refine features from the underlying data and build pipelines to train and deploy models.
  • Partner with data scientists to understand, implement, refine and design machine learning and other algorithms.
  • Run regular A/B tests, gather data, perform statistical analysis, draw conclusions on the impact of your models.
  • Work cross functionally with product managers, data scientists and product engineers, and communicate results to peers and leaders.
  • Explore new technology shifts in order to determine how they might connect with the customer benefits we wish to deliver.

Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing pay equity for employees, Intuit conducts regular comparisons across categories of ethnicity and gender.

Qualifications
  • BS, MS, or PhD degree in Computer Science or related field, or equivalent work experience.
  • 6+ years of experience
  • Knowledgeable with Data Science tools and frameworks (i.e. Python, Scikit, NLTK, Numpy, Pandas, TensorFlow, Keras, R, Spark).
  • Basic knowledge of machine learning techniques (i.e. classification, regression, and clustering).
  • Understand machine learning principles (training, validation, etc.)
  • Knowledge of data query and data processing tools (i.e. SQL)
  • Computer science fundamentals: data structures, algorithms, performance complexity, and implications of computer architecture on software performance (e.g., I/O and memory tuning).
  • Software engineering fundamentals: version control systems (i.e. Git, Github) and workflows, and ability to write production-ready code.
  • Experience deploying highly scalable software supporting millions or more users
  • Experience with GPU acceleration (i.e. CUDA and cuDNN)
  • Experience with integrating applications and platforms with cloud technologies (i.e. AWS and GCP)
  • Strong oral and written communication skills. Ability to conduct meetings and make professional presentations, and to explain complex concepts and technical material to non-technical users

Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position will be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs. The expected base pay range for this position is: Bay Area, CA: $197,000 - $266,500.

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