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Machine Learning Quantum Computing Jobs (NOW HIRING)

Amazon

Machinist, Quantum Computing

Pasadena, CA · On-site

$23.75 - $32.50/hr

In this role, you will support the CNC machine shop with parts production and day-to-day shop ... The ideal candidate demonstrates a strong commitment to continuous learning and professional growth ...

Amazon

Machinist, Quantum Computing

Pasadena, CA

$23.75 - $32.50/hr

In this role, you will support the CNC machine shop with parts production and day-to-day shop ... The ideal candidate demonstrates a strong commitment to continuous learning and professional growth ...

Amazon

Machinist, Quantum Computing

Pasadena, CA · On-site

$23.75 - $32.50/hr

In this role, you will support the CNC machine shop with parts production and day-to-day shop ... The ideal candidate demonstrates a strong commitment to continuous learning and professional growth ...

Umd

ARLIS Quantum Research Professional

College Park, MD

$17.75 - $24.50/hr

... intelligence / machine learning, quantum science, and human-machine teaming. Researchers ... Critically evaluating the utility of emerging quantum computing, sensing, and networking ...

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All JobsMachine Learning Quantum Computing Jobs

Machine Learning Quantum Computing information

See salary details

$25.5K

$42.6K

$88K

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

As of Jul 11, 2026, the average yearly pay for machine learning quantum computing in the United States is $42,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 per year, depending on experience, location, and employer.

What is the difference between Machine Learning Quantum Computing vs Data Scientist?

AspectMachine Learning Quantum ComputingData Scientist
Required CredentialsAdvanced degrees in quantum computing, machine learning, or related fieldsDegree in data science, statistics, or computer science
Work EnvironmentResearch labs, tech companies focusing on quantum tech, academiaBusiness environments, tech companies, consulting firms
Industry UsageEmerging quantum tech industry, research institutionsFinance, healthcare, marketing, e-commerce
Common Search/ComparisonQuantum algorithms, quantum machine learningData analysis, predictive modeling

Machine Learning Quantum Computing specialists focus on developing algorithms that leverage quantum mechanics to enhance machine learning tasks, often requiring advanced knowledge of quantum physics. Data Scientists analyze and interpret large datasets using traditional machine learning techniques. While both roles involve machine learning, the former emphasizes quantum computing applications, whereas the latter centers on data analysis in conventional computing environments.

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

To thrive in Machine Learning Quantum Computing, you need strong foundations in quantum mechanics, linear algebra, and advanced machine learning concepts, typically supported by a degree in physics, computer science, or a related field. Familiarity with quantum programming languages (such as Qiskit or Cirq), cloud-based quantum platforms, and proficiency in Python are usually required, alongside experience with relevant certifications or coursework. Strong problem-solving skills, adaptability, and effective collaboration are vital soft skills in this interdisciplinary field. These competencies are crucial for driving innovation and bridging the gap between quantum computing and practical machine learning applications.

How do professionals in Machine Learning Quantum Computing typically collaborate with interdisciplinary teams?

Professionals in Machine Learning Quantum Computing often work closely with experts in physics, computer science, and engineering. Collaboration usually involves translating quantum concepts for machine learning specialists and vice versa, ensuring that algorithms are both theoretically sound and practically implementable on quantum hardware. Regular meetings, code reviews, and knowledge-sharing sessions are standard, as interdisciplinary insight is crucial for advancing research and developing scalable solutions. Effective communication and a willingness to learn from other domains are essential for success in these teams.

What is Machine Learning Quantum Computing?

Machine Learning Quantum Computing is an interdisciplinary field that combines principles of quantum computing with machine learning techniques. It aims to leverage the computational power of quantum computers to enhance the performance of machine learning algorithms, potentially solving complex problems more efficiently than classical computers. This area includes developing quantum algorithms for tasks such as classification, clustering, and optimization, as well as using machine learning to improve quantum hardware and error correction. Researchers expect that, as quantum hardware matures, this field could revolutionize data analysis, cryptography, and scientific discovery.
More about Machine Learning Quantum Computing jobs
What cities are hiring for Machine Learning Quantum Computing jobs? Cities with the most Machine Learning Quantum Computing job openings:
What states have the most Machine Learning Quantum Computing jobs? States with the most job openings for Machine Learning Quantum Computing jobs include:
What job categories do people searching Machine Learning Quantum Computing jobs look for? The top searched job categories for Machine Learning Quantum Computing jobs are:
Machine Learning Quantum Computing jobs near you
Infographic showing various Machine Learning Quantum Computing job openings in the United States as of July 2026, with employment types broken down into 90% Full Time, 9% Part Time, and 1% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.
Quantum Calibration Engineer, Quantum Computing Services

Quantum Calibration Engineer, Quantum Computing Services

QuEra Computing, Inc.

Boston, MA • On-site

$120K - $180K/yr

Full-time

Re-posted 23 days ago

Job description

Quantum Calibration Engineer, Quantum Computing Services
Summary:
QuEra is seeking Quantum Calibration Engineers to join a growing effort focused on developing, testing and deploying calibration and performance characterization software on QuEra's neutral-atom quantum computers, translating experimental physics and data analysis into automation. This is a critical effort towards achieving programmability, reliability and peak performance of these machines for research, application development and commercial uses. Your work will directly shape how QuEra's quantum computers are characterized, stabilized, and improved over time, laying the foundation for scalable, self-calibrating quantum platforms.
In this role, you will work closely with physicists, software engineers, hardware specialists and actual quantum computers across QuEra's global sites. You will be responsible for designing efficient measurements of key system parameters, developing robust data-analysis pipelines, and building tools that translate raw experimental results into actionable insights for machine optimization.
This role is part of QuEra's Quantum Computing Services team and is based at QuEra's Boston headquarters. The team's mission is to develop QuEra's neutral-atom technology into cutting-edge quantum computing products and services.
Core Responsibilities
  • Design data-efficient experimental routines, robust data analyses and troubleshooting workflows to extract key system parameters and insights.
  • Develop, refine, and maintain calibration pipelines consisting of complex data flows.
  • Develop robust data-fitting and optimization routines.
  • Validate, document and track calibration results, ensuring reproducibility and traceability across different hardware and software generations, and across machine deployments.

Qualifications
Required
  • Strong proficiency in Python, including experience with data analysis and visualization libraries (e.g., NumPy, SciPy, Pandas, Matplotlib).
  • Hands-on experience working with real experimental or measurement data, including noise handling, curve fitting, and model validation.
  • Familiarity with optimization and regression techniques, both classical (e.g., least-squares, nonlinear fits) and statistical (e.g., Bayesian inference, parameter estimation).
  • Comfort working in a hardware-facing environment, integrating software with lab instruments, data acquisition systems, or experimental control frameworks.
  • Solid understanding of version control (Git) and structured software development practices (testing, modularity, documentation).
  • Strong problem-solving ability, scientific curiosity, and a willingness to learn new physical systems quickly.
  • Eager to grow from a capable engineer into a domain expert in quantum device
  • Enjoys hands-on experimentation, iteration, and uncovering structure in data.
  • Comfortable working across abstraction layers, from analyzing raw voltage traces to designing experiment-level calibration strategies.
  • Collaborative and adaptable; able to operate in an interdisciplinary environment spanning science, software, and hardware teams.

Nice to have
  • Experience with machine learning or data-driven modeling (e.g., for pattern recognition, drift prediction, or parameter inference).
  • Exposure to experimental physics or optics in a lab environment.
  • Theory and practice of control systems.
  • Familiarity with Kubernetes, Docker, or distributed analysis systems for scaling calibration and data pipelines.
  • Knowledge of signal processing and time-series analysis for extracting trends or correlations in data.
  • Proficiency in C or C++.

Education & Experience
  • Bachelor's or Master's degree in Physics, Electrical Engineering, Computer Science, Applied Mathematics, or a related quantitative field.
  • Candidates with diverse or nontraditional backgrounds who demonstrate strong programming and analytical skills are encouraged to apply.
  • Experience or exposure to experimental research, data-driven system optimization, or hardware-software integration (through research, internships, or personal projects) is a strong plus.

The approximate base salary range for this position is $120,000 - $180,000.
We consistently monitor external market data and update base salary ranges accordingly. We determine base compensation decisions on several factors, including as geographic placement, role-specific knowledge, skills, and/or experience. In addition to our base salary offerings, we also provide equity grants for all new hires.
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QuEra is committed to cultivating a diverse work environment and is proud to be an equal opportunity employer. We highly value diversity in our current and future employees and do not discriminate (including in our hiring and promotion practices) based on race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by law.

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