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Quantum Machine Learning Engineer Jobs in Irvine, CA

Machine Learning Scientist

Irvine, CA ยท On-site

$140 - $200/hr

# Machine Learning ScientistIrvine, CA**Full Time -- In Office -- Irvine, CA**## About Steg.AISteg.AI ... Collaborate with the engineering team to deploy models to customers* Benchmark new models versus ...

Sr Engineer, AI/Machine Learning

Irvine, CA ยท On-site

$140K - $170K/yr

Experience with machine learning libraries and modern frameworks such as PyTorch, Tensor flow, Keras, scikit-learn, etc. * Strong programming skills in MATLAB/Python/C/C++ and exposure to software ...

Experience with machine learning libraries and modern frameworks such as PyTorch, Tensor flow, Keras, scikit-learn, etc. * Strong programming skills in MATLAB/Python/C/C++ and exposure to software ...

Senior Machine Learning Platform Engineer

Irvine, CA ยท On-site

$110K - $152K/yr

The Senior Machine Learning Platform Engineer will design and manage scalable ML infrastructure, develop cloud-based pipelines, and ensure the reliability of MLOps workflows while mentoring junior ...

AI/ML Developer

Long Beach, CA ยท On-site

$140K - $160K/yr

DASSAULT SYSTEMES is seeking an AI / Machine Learning Engineer to join our R&D organization. This individual will contribute to the design, development, and continuous improvement of generative AI ...

Senior Machine Learning Platform Engineer

Irvine, CA ยท On-site

$112K - $154K/yr

We go beyond typical data-driven approaches or pure transformer-only architectures, combining rigorous engineering with learning systems proven in globally deployed solutions that deliver results ...

Showing results 41-60

Quantum Machine Learning Engineer information

See Irvine, CA salary details

$33.8K

$138.2K

$207.7K

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

As of Sep 3, 2026, the average yearly pay for quantum machine learning engineer in Irvine, CA is $138,220.00, according to ZipRecruiter salary data. Most workers in this role earn between $108,900.00 and $166,400.00 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 are popular job titles related to Quantum Machine Learning Engineer jobs in Irvine, CA?

For Quantum Machine Learning Engineer jobs in Irvine, CA, the most frequently searched job titles are:

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

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

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

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

Infographic showing various Quantum Machine Learning Engineer job openings in Irvine, CA as of June 2026, with employment types broken down into 86% Full Time, 12% Part Time, and 2% Contract. Highlights an 67% Physical, 4% Hybrid, and 29% Remote job distribution, with an average salary of $138,220 per year, or $66.5 per hour.

Senior Machine Learning Engineer

Menlo Ventures

Costa Mesa, CA โ€ข On-site

$100 - $130/hr

Other

Medical, Dental, Retirement, PTO

Posted 15 days ago


Job description

About Kinetic

Kinetic Automation is building a network of automated repair centers for modern vehicles. The auto industry is transitioning from mechanically complex vehicles to mechanically simple ones with complex software and technology. Kinetic aims to be the primary infrastructureโ€‘asโ€‘aโ€‘service for servicing future vehicles with our robotic repair centers, powered by our proprietary software and AI. We are a strong team of experienced robotics, automotive and shared mobility enthusiasts who have worked in selfโ€‘driving, mapping, lidar, motorsport, and rideโ€‘sharing. We are a ventureโ€‘backed startup (Series B) with a clear goโ€‘toโ€‘market strategy and meaningful revenue.

About the role

You will be a part of a small, productionโ€‘minded ML team based in Orange County/Oakland. Youโ€™ll collaborate with other engineers and researchers to develop, evaluate, and help deploy vision models for tasks like semantic/instance segmentation and object/damage detection across 2D and 3D data.

Experience & Skills Required
  • Deep ML / CV Fundamentals: You need handsโ€‘on experience training and evaluating deep models for segmentation and detection (PyTorch). You must understand how Transformer/LLM building blocks map to vision (ViT/DETR/Mask2Former) and have practical exposure to 2D/3D data, point clouds, and camera geometry.
  • Curiosity & Strict Attention to Detail: You are obsessed with corner cases. You have a sharp eye for data anomalies, run rigorous ablations, keep meticulous experiment logs, and can clearly communicate tradeโ€‘offs.
  • AIโ€‘Empowered, Not AIโ€‘Dependent: We strongly encourage leveraging AI tools (Copilot, ChatGPT, Claude) to maximize your efficiency. However, you must 100% understand the underlying details of the code you ship. We are looking for strong independent thinkers and debuggers, not someone who simply passes along AI outputs without deep comprehension.
  • Transformer and LLM building blocks applied to vision: Working knowledge of transformer and LLM building blocks applied to vision, including selfโ€‘attention, positional encodings, tokenization, and mapping these ideas to vision models (e.g., ViT, DETR, Mask2Former).
  • Practical exposure to 3D/depth data, including familiarity with point clouds, camera geometry (intrinsics/extrinsics), basic calibration, and multiโ€‘view geometry.
  • Proficiency in Python and the relevant tech stack: PyTorch, torchvision, Detectron2 or MMDetection/Segmentation, and Hugging Face Transformers.
  • Experience with Python services (FastAPI/Flask), Docker, and AWS services (S3, Batch/EC2, ECR) is preferred.
  • Strong communication skills with the ability to write tidy PRs, experiment logs, and short design notes to ensure reproducibility.
Responsibilities
  • The Work: Implement training loops, curate datasets, drive highโ€‘priority experiments, and partner with crossโ€‘functional teams to close feedback loops from edge cases.
  • The Stack: PyTorch, Detectron2 / MMDetection / Segmentation, Hugging Face Transformers, Python (FastAPI), Docker, AWS.
  • Collaborate on model development by implementing training loops, losses, augmentations, and evaluations using PyTorch.
  • Keep current with the industry by summarizing relevant papers and PRs, and proposing small, testable improvements.
  • Contribute to datasets by helping define labeling guidelines, curating splits, running quality checks, and maintaining data versioning.
  • Run experiments to track metrics, perform ablations, write clear experiment notes, and present findings.
  • Provide production support by exporting models, writing basic inference code, adding tests, and assisting with performance profiling.
  • Work crossโ€‘functionally, partnering with backend engineers on APIs, containers, and CI, and with ops/labeling teams on edge cases and feedback loops.
Benefits
  • Competitive salary and equity package.
  • Comprehensive health and dental insurance.
  • Retirement savings plan.
  • Paid time off and holidays.

Kinetic is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate based on race, color, religion, gender, gender expression, age, national origin, disability, marital status, sexual orientation, military status, or any protected attribute. We encourage qualified candidates from all backgrounds to apply and join us in our mission. If you require accommodation at any stage of the application process due to a disability, please let us know.

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