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Quantum Machine Learning Engineer Jobs (NOW HIRING)

Machine Learning Engineer (Molecular Design) Location: Hybrid - Bay Area, CA We are seeking a Machine Learning Engineer with expertise in molecular design to support cutting-edge drug discovery ...

REMOTE Machine Learning Engineer This project-based consulting role invites an experienced Machine Learning Engineer to apply advanced analytical, statistical, and software engineering expertise to ...

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 ...

Machine Learning Engineer / Research Engineer Pay: $$110,000 - $165,000 Base Salary + Equity Shift: N/A Location: San Mateo, CA (Peninsula) - Onsite Preferred Schedule: Full time, Permanent Role Visa ...

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 ...

About the role: We're looking for an early career Machine Learning Engineer to join our team. In this role you will build and deploy state of the art machine learning models to solve complex ...

W2 Candidates Only We are seeking a Machine Learning Engineer to develop, deploy, and optimize machine learning models and AI solutions. The ideal candidate will have strong experience with Python ...

Job Title Machine Learning Engineer Location Remote Rate $48/hr on W2 Must Haves: Neaural networks NLP Python AZURE Pytorch or tensorflow Machine Learning Engineer / AI Engineer Role Role Overview ...

About the role: We're looking for an early career Machine Learning Engineer to join our team. In this role you will build and deploy state of the art machine learning models to solve complex ...

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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 Sep 5, 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 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.
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What cities are hiring for Quantum Machine Learning Engineer jobs?

Cities with the most Quantum Machine Learning Engineer job openings:

What states have the most Quantum Machine Learning Engineer jobs?

States with the most job openings for Quantum Machine Learning Engineer jobs include:

Infographic showing various Quantum Machine Learning Engineer job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 24% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $128,769 per year, or $61.9 per hour.

Machine Learning Engineer

3B Staffing LLC

Tahoma, CA • On-site

Full-time

Posted 4 days ago


Job description

Job Title: Machine Learning Engineer (Molecular Design)
Location: Hybrid - Bay Area, CA

Job Description:
We are seeking a Machine Learning Engineer with expertise in molecular design to support cutting-edge drug discovery initiatives. The role focuses on developing and optimizing ML workflows for molecular property prediction and generative modeling to accelerate research and innovation.

Key Responsibilities:

  • Develop and implement machine learning models for molecular property prediction and generative molecular design.
  • Collaborate with cross-functional teams to integrate ML workflows into drug discovery pipelines.
  • Analyze and interpret complex molecular datasets to guide experimental design.
  • Stay up-to-date with the latest research and publications in molecular modeling and computational chemistry.

Qualifications:

  • 3-5 years of experience in machine learning, computational chemistry, or molecular modeling, or a PhD with relevant publications in molecular design.
  • Strong programming skills in Python and familiarity with ML frameworks (e.g., PyTorch, TensorFlow).
  • Hands-on experience with generative models, predictive modeling, and molecular simulations.
  • Excellent analytical, problem-solving, and communication skills.

Preferred:

  • Experience in drug discovery or pharmaceutical research environments.
  • Familiarity with cheminformatics tools and molecular libraries.