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Machine Learning Quantum Computing Jobs in Massachusetts

QuEra Computing, Inc.

Optical Scientist - R&D

Boston, MA · On-site

$130K - $211K/yr

Improve the performance, and operability of existing proof-of-concept quantum computing machines. * Collaborate with scientists and engineers across disciplines to develop and refine new experimental ...

IBM

Staff Quantum Algorithm Theorist

Cambridge, MA · On-site

Exploring what's next in computing and shaping the technologies the world will rely on tomorrow ... Our IBMers are growth minded, always staying curious, open to feedback and learning new information ...

IBM

Quantum algorithm developer

Cambridge, MA · On-site

Exploring what's next in computing and shaping the technologies the world will rely on tomorrow ... Our IBMers are growth minded, always staying curious, open to feedback and learning new information ...

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Machine Learning Quantum Computing information

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.

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

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 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 popular job titles related to Machine Learning Quantum Computing jobs in Massachusetts?

For Machine Learning Quantum Computing jobs in Massachusetts, the most frequently searched job titles are:

What job categories do people searching Machine Learning Quantum Computing jobs in Massachusetts look for?

The top searched job categories for Machine Learning Quantum Computing jobs in Massachusetts are:

What cities in Massachusetts are hiring for Machine Learning Quantum Computing jobs?

Cities in Massachusetts with the most Machine Learning Quantum Computing job openings:

Machine Learning Quantum Computing jobs near you
Infographic showing various Machine Learning Quantum Computing job openings in Massachusetts as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 18% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Optical Scientist - R&D

QuEra Computing, Inc.

Boston, MA • On-site

$130K - $211K/yr

Full-time

Re-posted 24 days ago

Job description

Summary

QuEra Computing is pioneering the future of quantum computing technology. We are seeking an Optical Scientist to join our growing team and help create the world's largest and first commercially relevant quantum computing platform. You will work closely with a world-class team of scientists, engineers, and developers to build and advance the most powerful neutral-atom quantum computers in the world. This is a hands-on experimental role at the intersection of atomic, molecular, and optical (AMO) physics and cutting-edge quantum hardware development.

Responsibilities

  • Design, prototype, and deploy opto-mechanical systems for next-generation quantum computing platforms, with a focus on hands-on experimental implementation in a lab environment.
  • Characterize, optimize, and troubleshoot precision laser and imaging optical systems, ensuring performance meets the demanding requirements of neutral-atom quantum processors.
  • Improve the performance, and operability of existing proof-of-concept quantum computing machines.
  • Collaborate with scientists and engineers across disciplines to develop and refine new experimental concepts and optical architectures.
  • Contribute to the development of experimental procedures, documentation, and best practices to support reliable and repeatable system performance.

Qualifications

  • Ph.D. in Atomic, Molecular, and Optical (AMO) Physics or a closely related field.
  • 3-6 years of hands-on experimental experience in precision optical systems, opto-mechanical design, or laser systems, including industry or postdoctoral experience.
  • Strong practical skills with precision laser systems, optical components, and imaging systems in a lab setting.
  • A collaborative mindset and enthusiasm for working in highly interdisciplinary teams.

Preferred Qualifications

  • Experience with neutral-atom, ion trap, or other quantum computing or quantum sensing platforms.
  • Familiarity with opto-mechanical design tools and practices.
  • Strong project management and organizational skills.
  • Experience translating experimental concepts into robust, deployable hardware.

The approximate base salary range for this position is $130,400 - $211,900.

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.

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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