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Quantum Machine Learning Engineer Jobs (NOW HIRING)

AI Squared

Machine Learning Engineer

Washington, DC · On-site

Machine Learning Engineer Washington, DC (Hybrid) About the Role: We are seeking a highly skilled Machine Learning Engineer to join our core AI team. In this role, you will focus on deploying ...

Roberts Recruiting

Machine Learning Engineer

Boston, MA · On-site

As a machine learning engineer, you will develop natural language processing systems that help our customers understand their contracts. You will work with a wide range of structured and unstructured ...

Constellation Space

Machine Learning Engineer

Seattle, WA · On-site

$120K - $180K/yr

The Role We are looking for a Machine Learning Engineer to bridge the gap between AI research and production-grade flight systems. You will optimize, deploy, and scale machine learning models that ...

Givzey

Machine Learning Engineer

Machine Learning Engineer We're looking for a talented and motivated Machine Learning Engineer to join our team and help develop cutting-edge AI solutions. In this role, you'll have the opportunity ...

Cymertek

Machine Learning Engineer

Aurora, CO · On-site

Machine Learning Engineer LOCATION Aurora, CO 80014 CLEARANCE TS/SCI Full Poly (Please note this position requires full U.S. Citizenship) KEY SUMMARY We are seeking a talented and innovative Machine ...

Winaxis

Machine Learning Engineer

Fremont, CA · On-site

Machine Learning Engineer Location: Fremont, CA (Local) Onsite interview Duration: 12+ Mos H1B Only h1 candidate About the Role: Our direct client is hiring a Machine Learning Engineer for their ...

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Quantum Machine Learning Engineer information

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$31.5K

$128.8K

$193.5K

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

As of Jul 4, 2026, the average yearly pay for quantum machine learning engineer in the United States is $128,769.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,500.00 and $155,000.00 per year, depending on experience, location, and employer.

What is the salary of quantum machine learning engineer?

The salary of a quantum machine learning engineer typically ranges from $100,000 to $150,000 annually, depending on experience, education, and location. Senior roles or those with specialized skills in quantum algorithms and programming languages like Python or Qiskit may offer higher compensation. Many positions also include benefits such as research opportunities and access to advanced quantum computing tools.

What engineers make $500,000?

Senior engineers in specialized fields such as software engineering, data engineering, or engineering management can earn $500,000 or more annually, especially with extensive experience, advanced skills, and in high-demand industries like technology or finance. Compensation often includes base salary, bonuses, and stock options, particularly at large tech companies or startups with significant growth potential.

Is quantum machine learning a good career?

Quantum machine learning engineers work at the intersection of quantum computing and machine learning, developing algorithms that leverage quantum hardware. The field is emerging, with high demand for specialized skills in quantum algorithms, programming languages like Qiskit, and understanding of both quantum physics and data science. Careers in this area can be rewarding but often require advanced education and continuous learning due to rapid technological advancements.

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.

Will MLE be replaced by AI?

Quantum Machine Learning Engineers work at the intersection of quantum computing and machine learning, developing algorithms that leverage quantum systems. While AI continues to advance, quantum computing is expected to complement classical machine learning rather than replace it entirely, and MLE roles will evolve to incorporate new quantum techniques and tools. Continuous learning in both quantum algorithms and machine learning is essential for professionals in this field.

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.

What are the key skills and qualifications needed to thrive as a Quantum Machine Learning Engineer, and why are they important?

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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Quantum Machine Learning Engineer jobs near you
Infographic showing various Quantum Machine Learning Engineer job openings in the United States as of June 2026, with employment types broken down into 87% Full Time, 11% Part Time, and 2% Contract. Highlights an 67% Physical, 4% Hybrid, and 29% Remote job distribution, with an average salary of $128,769 per year, or $61.9 per hour.

Machine Learning Engineer

Waypoint Human Capital

Huntsville, AL • On-site

Full-time

This job post has expired 2 days ago. Applications are no longer accepted.

Job description

Position Title: Machine Learning Engineer
Position Type: Full-time, On-Site
Location: Huntsville, AL
Clearance: Active TS
Description:
Waypoint's client is seeking a Machine Learning Engineer to support mission-critical efforts within a secure environment at the Missile and Space Intelligence Center. This role focuses on developing, integrating, and operationalizing machine learning solutions that support advanced analytics and intelligence capabilities.
The selected candidate will work across the full machine learning lifecycle, from building data pipelines and training models to deploying and monitoring production systems. This position requires a strong blend of software engineering and data science expertise, with a focus on scalability, performance, and system integration.
Responsibilities:
• Integrate machine learning systems into existing software architectures and enterprise platforms
• Design, build, and optimize data pipelines to support model training and inference
• Develop, test, and deploy machine learning models into production environments
• Manage transition from prototype to production, including deployment pipelines and monitoring solutions
• Monitor model performance, including handling model drift, rollback, and failure scenarios
• Conduct experiments and testing to evaluate and improve model accuracy and performance
• Write clean, maintainable, and testable code in Python and related technologies
• Collaborate with cross-functional teams to integrate ML capabilities into mission systems
• Utilize CI/CD pipelines and GitOps practices to support automated deployment and version control
• Support development in Linux and Windows environments
Required:
• Active TS clearance (with ability to obtain TS/SCI with CI Polygraph)
• Bachelor's degree in Computer Science, Mathematics, Statistics, Physics, or related technical field
• Minimum 12+ years of overall experience, including 1-3 years working with machine learning frameworks
• Strong programming skills in Python
• Experience with machine learning frameworks, libraries, and data modeling techniques
• Solid understanding of the machine learning lifecycle
• Experience working with SQL and NoSQL databases
• Experience working in Linux and Windows environments
• Familiarity with CI/CD pipelines and Agile development methodologies
• Understanding of software design and system integration principles
Desired:
• Active TS/SCI with CI Polygraph (desired)
• Experience working with large-scale (petabyte-level) datasets
• Experience supporting multi-INT analytics environments
• Experience deploying, monitoring, and scaling machine learning models in production
• Experience with tools such as Docker, Jupyter Notebooks, PostgreSQL, GitLab, and GitHub
• Experience implementing GitOps workflows
• Experience working in secure or classified environment

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