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Quantum Machine Learning Engineer Jobs in Massachusetts

Senior Machine Learning Engineer

Boston, MA · On-site +1

$133K - $175K/yr

Position Summary The Machine Learning Engineer will be responsible for the end-to-end development and deployment of Large language and machine learning models, with a primary focus on data ...

Senior Machine Learning Engineer Job Duties: Design and implement image processing solutions to enhance operational workflows and fraud detection. Duties include: * Design, develop, and maintain AI ...

The Core for Computational Biomedicine (CCB) in the Department of Biomedical Informatics (DBMI) at Harvard Medical School (HMS) is looking for a Machine Learning Engineer with advanced expertise to ...

Machine Learning Engineer

Woburn, MA · On-site

$115K - $140K/yr

The Role As a Machine Learning Engineer, you will help develop and integrate cutting-edge AI/ML models into production systems that solve critical national security problems. Working as part of a ...

The Role As a Machine Learning Engineer, you will help develop and integrate cutting-edge AI/ML models into production systems that solve critical national security problems. Working as part of a ...

Machine Learning Engineer

Woburn, MA · On-site

$115 - $140/hr

The Role As a Machine Learning Engineer, you will help develop and integrate cutting-edge AI/ML models into production systems that solve critical national security problems. Working as part of a ...

The Role As a Machine Learning Engineer, you will help develop and integrate cutting-edge AI/ML models into production systems that solve critical national security problems. Working as part of a ...

Machine Learning Engineer

Woburn, MA · On-site

$115K - $140K/yr

The Role As a Machine Learning Engineer, you will help develop and integrate cutting-edge AI/ML models into production systems that solve critical national security problems. Working as part of a ...

Software Machine Learning Engineer

Reading, MA · On-site

$116.50 - $186.40/hr

Software Machine Learning Engineer Location: North Reading, MA, US Our Purpose TERADYNE, where experience meets innovation and driving excellence in every connection. We are fueled by creativity and ...

Showing results 21-40

Quantum Machine Learning Engineer information

See Massachusetts salary details

$34.4K

$140.6K

$211.3K

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

As of Aug 12, 2026, the average yearly pay for quantum machine learning engineer in Massachusetts is $140,632.00, according to ZipRecruiter salary data. Most workers in this role earn between $110,800.00 and $169,300.00 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.

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?

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.
What are popular job titles related to Quantum Machine Learning Engineer jobs in Massachusetts? For Quantum Machine Learning Engineer jobs in Massachusetts, the most frequently searched job titles are:
What job categories do people searching Quantum Machine Learning Engineer jobs in Massachusetts look for? The top searched job categories for Quantum Machine Learning Engineer jobs in Massachusetts are:
What cities in Massachusetts are hiring for Quantum Machine Learning Engineer jobs? Cities in Massachusetts with the most Quantum Machine Learning Engineer job openings:
Infographic showing various Quantum Machine Learning Engineer job openings in Massachusetts as of August 2026, with employment types broken down into 100% Full Time. Highlights an 74% In-person, and 26% Remote job distribution, with an average salary of $140,632 per year, or $67.6 per hour.

Senior Machine Learning Engineer

C the Signs

Boston, MA • On-site, Remote

$133K - $175K/yr

Full-time

Re-posted 16 days ago


Job description

Position Summary
The Machine Learning Engineer will be responsible for the end-to-end development and deployment of Large language and machine learning models, with a primary focus on data preprocessing, model training, and fine-tuning using large-scale healthcare datasets. This role requires a strong understanding of Large language models, machine learning principles, data engineering, and experience working with sensitive healthcare data.
Key Responsibilities
  • Data Preprocessing: Clean, transform, and prepare large, complex healthcare datasets for machine learning model development. This includes handling missing values, outlier detection, feature engineering, and data normalization. Identify, collect, and curate relevant, industry-specific datasets for model retraining. Format data appropriately for the chosen LLM and training pipeline
  • Model Training & Fine-Tuning: Design, train, and fine-tune various LLMs on extensive healthcare data to solve specific clinical or operational problems. Set up and manage the training environment, including GPU instances and required software. Train and fine-tune pre-trained LLMs on the custom dataset to achieve specific goals. Experiment with and fine-tune hyperparameters such as learning rate, batch size, and training epochs to optimize model performance. Integration of structured + unstructured data (multi-modal/multi-input models)
  • Model Evaluation & Optimization: Evaluate model performance using appropriate metrics, identify areas for improvement, and implement optimization strategies.
  • Pipeline Development: Develop and maintain robust and scalable data and ML pipelines for model training, inference, and deployment.
  • Collaboration: Work closely with data scientists, clinicians, and software engineers to understand requirements, integrate models into production systems, and ensure data privacy and security compliance.
  • Research & Development: Stay up-to-date with the latest advancements in machine learning and healthcare AI, and explore new technologies and methodologies to enhance our solutions.
  • Documentation: Maintain clear and comprehensive documentation of models, data pipelines, and experimental results.

Requirements
  • Education: Bachelor's or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, or a related quantitative field.
  • Experience:
    • 5+ years of experience in Machine Learning Engineering or a similar role.
    • Proven experience with large-scale data preprocessing, LLM/model training, and fine-tuning.
    • Experience with distributed training (PyTorch Distributed, DeepSpeed, Ray, Hugging Face Accelerate).
    • Experience with GPU/TPU optimization, memory management for large language models.
    • Experience working with healthcare data is highly desirable.
  • Technical Skills:
    • Proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn, Pandas, NumPy).
    • Strong understanding of various machine learning algorithms,Large Language Models, and deep learning architectures.
    • Experience with cloud platforms (e.g., GCP, AWS) and distributed computing frameworks (e.g., Spark) is a plus.
    • Familiarity with MLOps practices and tools.
  • Soft Skills:
    • Excellent problem-solving and analytical skills.
    • Strong communication and collaboration abilities.
    • Ability to work independently and as part of a team in a fast-paced environment.
  • Work Authorization:
      • Must be a US Citizen, Green Card holder, or currently in the US have valid H1B visa

Benefits
Why Join Us?
Joining C the Signs is not just about building AI; it's about shaping the future of healthcare. If you are a technical leader with an unshakable belief in the power of AI to save lives and the ability to make it happen at scale, this is your opportunity to create a tangible, global impact.
Benefits:
  • Competitive salary and benefits package.
  • Flexible working arrangements (remote or hybrid options available).
  • The opportunity to work on life-changing AI technology that directly impacts patient outcomes.
  • Join a team that combines cutting-edge innovation with a mission to save lives and improve health equity.
  • Continuous learning opportunities with access to the latest tools and advancements in AI and healthcare.