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Machine Learning Quantum Computing Jobs in Methuen, MA

NVIDIA

Senior HPC and Quantum Systems Engineer

Westford, MA · On-site

$108K - $148K/yr

... and machine learning. • Prototype and evaluate end-to-end workflows that demonstrate the ... NVIDIA is a computing platform company operating at the intersection of graphics, HPC, and AI.

Nvidia

Senior HPC and Quantum Systems Engineer

Westford, MA · Hybrid

$108K - $148K/yr

... and machine learning. * Prototype and evaluate end-to-end workflows that demonstrate the ... Familiarity with quantum computing concepts and hardware architectures (neutral atom, trapped ion ...

Nvidia

Senior HPC and Quantum Systems Engineer

Westford, MA · Hybrid

$108K - $148K/yr

... and machine learning. * Prototype and evaluate end-to-end workflows that demonstrate the ... Familiarity with quantum computing concepts and hardware architectures (neutral atom, trapped ion ...

Riverlane

Quantum Scientist - Applied QEC

Boston, MA

$135K - $170K/yr

Using your knowledge of quantum computing, you will help translate experimental goals into ... A learning environment that encourages individual, team and company growth and development ...

Riverlane

Quantum Scientist - Applied QEC

Boston, MA

$135K - $170K/yr

Using your knowledge of quantum computing, you will help translate experimental goals into ... A learning environment that encourages individual, team and company growth and development ...

Riverlane

Quantum Scientist - Applied QEC

Boston, MA · On-site

$135K - $170K/yr

Using your knowledge of quantum computing, you will help translate experimental goals into ... A learning environment that encourages individual, team and company growth and development ...

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 ...

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 ...

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All JobsMachine Learning Quantum Computing JobsMachine Learning Quantum Computing Jobs in Methuen, MA

Machine Learning Quantum Computing information

See Methuen, MA salary details

$26.7K

$44.5K

$92K

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

As of Jun 21, 2026, the average yearly pay for machine learning quantum computing in Methuen, MA is $44,521.00, according to ZipRecruiter salary data. Most workers in this role earn between $34,000.00 and $48,100.00 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.
What cities near Methuen, MA are hiring for Machine Learning Quantum Computing jobs? Cities near Methuen, MA with the most Machine Learning Quantum Computing job openings:
Machine Learning Quantum Computing jobs near you
Principal Systems Engineer - Quantum Computing Systems

Principal Systems Engineer - Quantum Computing Systems

QuEra Computing, Inc.

Boston, MA • On-site

Full-time

Posted 13 days ago

Job description

Summary
We are seeking a Principal Systems Engineer to play a critical role in aligning engineering execution with scientific and machine-level progress in the development of large-scale quantum computers.
This role sits at the intersection of quantum science, hardware engineering, and control software, with a primary mission to make the system coherent, buildable, and integrable as it evolves. Unlike traditional product environments, many system requirements in quantum computing are discovered through experimentation, not defined upfront. Success in this role requires deep collaboration with scientists, rapid learning, and the ability to introduce structure only where it accelerates progress.
The ideal candidate brings extensive experience building complex hardware-software systems (e.g., aerospace, EVs, robotics, advanced instrumentation) and is motivated to apply systems engineering rigor in a learning-driven R&D environment, pairing closely with internal quantum experts.
This is a technical leadership role with broad influence across teams. Authority comes from clarity, usefulness, and trust - not from gatekeeping or heavy process.
Core Mission
  • Bridge the gap between engineering tasks and quantum machine milestones
  • Make system architecture, integration status, and technical risk visible and actionable
  • Enable scientists and engineers to move faster together by reducing ambiguity, friction, and rework
  • Help the organization evolve from ad-hoc integration to disciplined, scalable system development - without slowing discovery

Responsibilities
1. System Understanding Through Scientific Partnership
  • Work closely and continuously with quantum scientists to understand how the machine is actually operated, tuned, and debugged in practice.
  • Spend significant time in the lab, observing experiments and participating in scientific discussions to absorb tacit system knowledge.
  • Treat scientists as primary system knowledge holders, approaching requirement gathering as a learning and synthesis exercise.
  • Build trust by accurately reflecting scientific intent and constraints in system models, requirements, and architectural decisions.

2. Requirements Co-Evolution & Traceability
  • Facilitate the co-evolution of system requirements as the machine progresses:
    • Start with lightweight, provisional requirements
    • Explicitly document uncertainty, assumptions, and open questions
    • Refine requirements as experimental results and understanding improve
  • Translate scientific goals (e.g., performance, stability, operability) into actionable engineering requirements while preserving necessary flexibility.
  • Establish traceability between:
    • machine-level goals
    • subsystem requirements
    • engineering deliverables (e.g., JIRA epics)
  • Ensure engineers understand the intent behind requirements, not just the wording.

3. System Architecture & Integration Leadership
  • Develop and maintain a living system architecture covering:
    • quantum hardware
    • control electronics and firmware
    • control software and orchestration layers
  • Produce clear, accessible architecture diagrams that reflect reality and evolve with the system.
  • Identify missing architectural elements, poorly defined interfaces, and integration risks early.
  • Lead system-level trade studies and technical decision-making in partnership with engineering and scientific leaders.
  • Ensure architecture reflects machine milestones and not just organizational boundaries.

4. Integration, Test Strategy, and Machine Protection
  • Define and drive a system integration and test strategy appropriate for an evolving R&D machine.
  • Help ensure engineering testbeds match machine configurations as closely as possible.
  • Push integration testing upstream so that machines are not used as primary test platforms.
  • Partner with engineering teams to define validation criteria tied to real machine behavior.
  • Reduce burden on lab teams by improving pre-deployment testing and integration readiness.

5. Early Wins & Trust Building
  • Deliver small, tangible improvements early that directly reduce friction for scientists and engineers, such as:
    • clarifying a recurring interface problem
    • creating a simple integration checklist
    • documenting a failure mode that saves days of debugging
  • Use these wins to establish credibility and reinforce the value of systems engineering.
  • Continuously gather feedback on what is helping vs. slowing teams down, and adapt approach accordingly.

6. Unlearning, Adaptation, and Process Design
  • Actively identify where traditional systems engineering assumptions do not apply to quantum computing.
  • Unlearn rigid models around fixed requirements, early design freezes, and linear development.
  • Introduce process and structure incrementally, calibrated to system maturity.
  • Champion systems thinking without dogma - prioritizing outcomes over formality.

7. Technical Leadership & Mentorship
  • Serve as a technical leader and mentor for engineers and emerging systems thinkers.
  • Help scale system knowledge through documentation, diagrams, and internal education.
  • Contribute to leadership discussions on technical strategy, integration risk, and execution pacing.

Qualifications
  • 10+ years of experience in systems engineering or system architecture for complex hardware-software systems.
  • Proven experience integrating multidisciplinary systems (hardware, software, controls).
  • Strong background in requirements definition, interface management, and system integration.
  • Ability to operate effectively in ambiguous, fast-evolving R&D environments.
  • Exceptional communication and collaboration skills.

Preferred Qualifications
  • Experience in aerospace, automotive, robotics, advanced instrumentation, or similar domains.
  • Familiarity with model-based systems engineering (MBSE) concepts or tools.
  • Experience working closely with research or experimental teams.
  • Exposure to quantum technologies is a plus, but not required.

Personal Attributes We Value
  • Intellectual humility and curiosity
  • Comfort learning from domain experts
  • Bias toward clarity and usefulness
  • Strong listening skills
  • Pragmatic, outcome-driven mindset

Why This Role Matters
You will help build a machine that has never existed before - not by enforcing process, but by making the system understandable, integrable, and scalable. This role is foundational to turning scientific breakthroughs into reliable quantum computers.
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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