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Quantum Machine Learning Engineer Jobs in Memphis, TN

Senior Data Engineer

Memphis, TN · On-site

$95K - $129K/yr

Senior Data Engineer Role Summary The Senior Data Engineer is responsible for designing, building ... Maintain Feature Store pipelines that produce machine learning-ready feature sets for model ...

Senior Data Engineer

Memphis, TN

$95K - $129K/yr

Senior Data Engineer Role Summary The Senior Data Engineer is responsible for designing, building ... Maintain Feature Store pipelines that produce machine learning-ready feature sets for model ...

AI Architect

Memphis, TN · On-site

$61.25 - $80.75/hr

With over sixty years of innovative engineering and manufacturing expertise, Meyer has helped to ... Research, prototype, and deploy modern AI technologies including Generative AI, Machine Learning ...

Data Science Tutor

Memphis, TN · Remote

$18 - $40/hr

Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning, data visualization, SQL, Python or R programming, hypothesis testing, and communication of data ...

AI Architect

Memphis, TN · On-site

$61.25 - $80.75/hr

With over sixty years of innovative engineering and manufacturing expertise, Meyer has helped to ... Research, prototype, and deploy modern AI technologies including Generative AI, Machine Learning ...

Excellent understanding and experience with application of machine learning concepts and techniques ... Must be proficient in programming either R/Python/Scala. * Should have experience in Financial ...

Python Tutor

Memphis, TN · Remote

$18 - $40/hr

Emphasizes readable, maintainable code and connects Python to machine learning, web scraping, scientific computing, and DevOps applications. * Curriculum Awareness & Adaptive Instruction: Familiar ...

... programming and SQL knowledge. * Demonstrated experience building and deploying statistical and machine learning models to address business challenges. * Skilled in data wrangling, quality evaluation ...

Showing results 21-40

Quantum Machine Learning Engineer information

See Memphis, TN salary details

$30.6K

$125.1K

$188K

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

As of Aug 23, 2026, the average yearly pay for quantum machine learning engineer in Memphis, TN is $125,094.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,600.00 and $150,600.00 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.

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.

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.

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 are popular job titles related to Quantum Machine Learning Engineer jobs in Memphis, TN?

For Quantum Machine Learning Engineer jobs in Memphis, TN, the most frequently searched job titles are:

What job categories do people searching Quantum Machine Learning Engineer jobs in Memphis, TN look for?

The top searched job categories for Quantum Machine Learning Engineer jobs in Memphis, TN are:

What cities near Memphis, TN are hiring for Quantum Machine Learning Engineer jobs?

Cities near Memphis, TN with the most Quantum Machine Learning Engineer job openings:

Senior Data Engineer

Intellivo

Memphis, TN • On-site

$95K - $129K/yr

Full-time

Re-posted 7 days ago


Job description

Senior Data Engineer
Role Summary
The Senior Data Engineer is responsible for designing, building, and optimizing scalable data pipelines and platform infrastructure within a medallion architecture (Bronze, Silver, Gold) on Microsoft Fabric and OneLake. This role delivers enterprise-grade ingestion, transformation, and enrichment solutions that convert raw healthcare, legal, and insurance data into structured intelligence signals used for identification scoring, analytics, and operational reporting.
The role requires deep experience with cloud data platforms, strong Python and SQL skills, and the ability to operate in a regulated healthcare environment with strict HIPAA compliance and multi-tenant data isolation requirements across a large portfolio of client contracts. This person will work closely with Data Science, ML Engineering, and Software Engineering teams to ensure reliable, governed, and performant data delivery across the organization.
Core Responsibilities
  • Data Ingestion Pipeline Development
    • Design and build data ingestion pipelines from multiple structured and unstructured sources including healthcare claims, P&C insurance data, and legal filings into the Bronze layer of the medallion architecture.
    • Optimize ingestion workflows for reliability, throughput, and compliance across regulated production environments.
    • Implement error handling, retry logic, and dead-letter patterns to ensure pipeline resilience.
  • Medallion Architecture and Transformation
    • Develop Silver layer transformation logic including normalization, deduplication, entity resolution, and schema enforcement within Microsoft Fabric and OneLake.
    • Build Gold layer aggregations and enriched datasets that support ML scoring models and embedded analytics reporting.
    • Maintain Feature Store pipelines that produce machine learning-ready feature sets for model training and inference.
  • Data Governance and Compliance
    • Enforce data contractual constraints from third-party data providers, including requirements for stateless processing and restrictions on data persistence or model training.
    • Implement multi-tenant data isolation patterns including partitioning, access controls, and governed data handling across a large number of client contracts.
    • Document data lineage, transformations, and data contracts to support governance, audit readiness, and operational clarity.
  • Data Quality and Monitoring
    • Build and maintain data quality validation scripts to detect schema drift, completeness gaps, and business-rule violations across pipeline stages.
    • Implement monitoring on pipeline health, data freshness, and operational exceptions to maintain high-confidence production data.
    • Establish alerting and escalation processes for pipeline failures and data anomalies.
  • Cross-Functional Collaboration
    • Partner with ML Engineering and Data Science to deliver features that support model retraining, scoring pipelines, and identification engine capabilities.
    • Collaborate with Software Engineering, Analytics, and business stakeholders to translate operational needs into reliable, production-ready data solutions.
    • Contribute to architectural decisions and technical documentation that support the broader data platform strategy.

Qualifications
Required
  • B.S. or B.A. in Computer Science, Information Systems, Mathematics, or a related field.
  • 7+ years of professional data engineering experience, preferably within Azure-based or Microsoft Fabric environments.
  • Hands-on experience designing enterprise data pipelines, ETL/ELT workflows, and medallion or lakehouse architecture patterns.
  • Strong programming skills in Python, with advanced SQL experience and data quality validation logic.
  • Experience with Microsoft Fabric, OneLake, Azure Data Factory, or equivalent cloud data orchestration tools.
  • Working knowledge of CI/CD practices for data pipelines and infrastructure-as-code concepts.
  • Demonstrated experience using AI-assisted development tools (e.g., GitHub Copilot, Cursor, or similar) to accelerate pipeline development, code generation, and debugging workflows.

Preferred
  • Familiarity with healthcare data formats (claims, eligibility, EDI 837/835) and HIPAA compliance requirements.
  • Experience with multi-tenant data architectures and governed data handling in regulated environments.
  • Exposure to ML feature engineering, Feature Store design, or data pipelines supporting model training workflows.
  • Experience with dbt, PySpark, or similar transformation frameworks.

Professional Skills
  • Highly organized with the ability to manage multiple concurrent technical workstreams.
  • Critical thinker with strong problem-solving ability and attention to detail.
  • Clear communicator, comfortable working asynchronously with distributed teams.
  • Self-directed with a track record of driving projects through completion without constant oversight.