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Quantum Machine Learning Engineer Jobs (NOW HIRING)

Job Summary We are seeking a Machine Learning Engineer with strong expertise in machine learning model development, data engineering, and modern cloud-based analytics platforms. This role will focus ...

Machine Learning Engineer - AI Data Trainer * Location: Remote About the job At Alignerr, we partner with the world's leading AI research teams and labs to build and train cutting-edge AI models.

Machine Learning Engineer

CA · On-site

$75 - $89/hr

Machine Learning Engineer Pay Rate: $75-$89/hour Position Summary We are seeking a skilled Machine Learning Engineer (MLOps) to support the full lifecycle of machine learning models, including design ...

They are seeking a Machine Learning Engineer to build systems that analyze the performance of music promotions, providing actionable insights for creators and partners. Responsibilities : • ...

Machine Learning Engineer Position: Full time Location: Carlsbad office About Us: NTENT provides a Platform-as-a-Service (PaaS), allowing industry partners to customize, localize and integrate search ...

Machine Learning Engineer Location: Detroit, MI- Onsite Type: Full-time Security Clearance: No clearance required, must be clearable. The Machine Learning Engineer will be an essential member of the ...

Spotify is a leading music streaming platform, and they are seeking a Machine Learning Engineer to join their Music Promotion team. The role involves building systems to understand the performance of ...

Machine Learning Engineer As a Machine Learning Engineer on the AI Platform team, you will design and build the foundational infrastructure that powers Docusign's next generation of intelligent ...

GCP/AWS Machine Learning Engineer Freddie Mac iLab is currently looking for Machine Learning Engineers in its Innovation Labs - Tech Strategy team. In this position, you will be responsible for ...

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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 Jun 13, 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 the salary of quantum machine learning engineer?

The salary of a quantum machine learning engineer typically ranges from $100,000 to $150,000 annually, depending on experience, education, and location. Senior roles or those with specialized skills in quantum algorithms and programming languages like Python or Qiskit may offer higher compensation. Entry-level positions generally start around $80,000 to $100,000.

What engineers make $500,000?

Senior engineers in specialized fields such as software engineering, data engineering, or engineering management can earn $500,000 or more annually, especially with extensive experience, advanced skills, and in high-demand industries like technology or finance. These roles often require advanced degrees, certifications, and leadership responsibilities.

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.

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.

Which 3 jobs will survive AI?

Quantum Machine Learning Engineers are likely to have resilient careers as their role combines advanced quantum computing and machine learning skills, which are less susceptible to automation. Jobs requiring complex problem-solving, creativity, and specialized expertise—such as data scientists, AI researchers, and cybersecurity analysts—are also expected to persist. These roles often involve tasks that are difficult for AI to fully automate and require ongoing human oversight and innovation.

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, and why are they important?

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.
More about Quantum Machine Learning Engineer jobs
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 June 2026, with employment types broken down into 40% Full Time, and 60% Part Time. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $128,769 per year, or $61.9 per hour.
Machine Learning Engineer

Machine Learning Engineer

Compunnel

Plano, TX • On-site

Contractor

Posted 12 days ago


Job description

Job Summary
We are seeking a Machine Learning Engineer with strong expertise in machine learning model development, data engineering, and modern cloud-based analytics platforms. This role will focus on building ML-ready data architectures, developing scalable machine learning solutions, and supporting enterprise analytics initiatives. The ideal candidate will possess hands-on experience with Azure Databricks, Python-based model development, Medallion Architecture, and MLOps practices, along with the ability to collaborate effectively with business and technical stakeholders.
Key Responsibilities
  • Design, develop, and maintain machine learning solutions that support advanced analytics and predictive modeling initiatives.
  • Build and optimize ML-ready data pipelines and data architectures using Medallion Architecture principles.
  • Develop and manage data ingestion, transformation, and curation processes across Bronze, Silver, and Gold data layers.
  • Create scalable feature engineering workflows and production-grade machine learning assets.
  • Design and implement machine learning pipelines using Azure Databricks and related cloud technologies.
  • Leverage Delta Lake, MLflow, and workflow orchestration tools to operationalize machine learning models and data transformations.
  • Develop and maintain Python-based machine learning models, feature engineering processes, and MLOps automation solutions.
  • Build and optimize SQL transformations, views, and ELT pipelines to support analytics and machine learning workloads.
  • Design and maintain feature stores, semantic layers, and curated datasets that support enterprise reporting and machine learning initiatives.
  • Integrate machine learning outputs into analytics platforms, dashboards, and business intelligence solutions.
  • Collaborate with business stakeholders, technical teams, and leadership to translate business requirements into scalable data and machine learning solutions.
  • Establish engineering standards, best practices, and scalable development processes for machine learning and data engineering initiatives.
  • Monitor data quality, model performance, and operational effectiveness of machine learning solutions.

Required Qualifications
  • 5-7 years of hands-on experience in machine learning engineering and data engineering.
  • 10+ years of experience delivering enterprise-scale data, analytics, and machine learning solutions.
  • Strong experience building machine learning models and supporting model development using Python.
  • Extensive experience with Azure Databricks for machine learning, feature engineering, and data engineering workloads.
  • Deep understanding of Medallion Architecture, including Bronze, Silver, and Gold data layer design and implementation.
  • Experience designing ML-ready data architectures and scalable data engineering solutions.
  • Experience migrating workloads to Databricks and implementing modern data platform architectures.
  • Hands-on experience with Delta Lake, MLflow, and Databricks Workflows.
  • Strong proficiency in Python for model development, feature engineering, and MLOps automation.
  • Advanced SQL skills with experience building optimized transformations, views, and ELT pipelines.
  • Experience designing feature stores, semantic models, and machine learning-ready datasets.
  • Strong understanding of machine learning lifecycle management, data engineering best practices, and scalable architecture patterns.
  • Ability to lead technical initiatives and establish engineering standards and development practices.
  • Strong business acumen and ability to communicate effectively with technical and business stakeholders.
  • Experience working in collaborative, fast-paced environments that encourage experimentation and innovation.

Preferred Qualifications
  • Experience working within Microsoft Azure cloud environments.
  • Experience integrating machine learning outputs into analytics platforms and business intelligence solutions.
  • Experience designing dashboards and reporting solutions that surface machine learning insights, data quality metrics, and model performance indicators.
  • Familiarity with Power BI, including DAX, semantic modeling, and visualization best practices.
  • Experience supporting enterprise-scale analytics, data science, and AI initiatives.
  • Experience mentoring technical teams and providing technical leadership on machine learning and data engineering projects.

Compunnel logo

About Compunnel

Sourced by ZipRecruiter

Compunnel is a well-known company located in Plainsboro, NJ, US, recognized in the industry of IT Services and Solutions. Established in 1989, Compunnel offers a suite of services that help businesses integrate technology efficiently into their operations, a recognizable name in the IT solutions sphere for over three decades. The company’s service portfolio includes Digital Transformation, Business Intelligence, Cloud Services, Cybersecurity, and Application Modern Services, among others. Guided by its mission "to innovate with industry-leading digital solutions and disruptive tech strategies for unimagining business growth," the company underlines its commitment to offering out-of-the-box solutions to its clients. Remarkable achievements of the company include serving more than 30 Fortune 500 companies and providing job opportunities for over 50,000 individuals.

Industry

It services

Company size

501 - 1,000 Employees

Headquarters location

Plainsboro, NJ, US

Year founded

1994

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