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Machine Learning Quantum Computing Jobs in Newcastle, OK

Varsity Tutors

Linear Algebra Tutor

Oklahoma City, OK · Remote

$40/hr

... machine learning, and quantum mechanics applications. * Curriculum Awareness & Adaptive Instruction ... vector spaces, computing determinants of large matrices, and grasping the significance of ...

Varsity Tutors

Python Tutor

Oklahoma City, OK · Remote

$40/hr

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

Varsity Tutors

Statics Tutor

Oklahoma City, OK · Remote

$40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for ... machines, centroids, moments of inertia, friction, and distributed forces. Ability to explain ...

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All JobsMachine Learning Quantum Computing JobsMachine Learning Quantum Computing Jobs in Newcastle, OK

Machine Learning Quantum Computing information

See Newcastle, OK salary details

$20.1K

$33.5K

$69.2K

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

As of May 29, 2026, the average yearly pay for machine learning quantum computing in Newcastle, OK is $33,504.00, according to ZipRecruiter salary data. Most workers in this role earn between $25,600.00 and $36,200.00 per year, depending on experience, location, and employer.

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 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.

Machine Learning Quantum Computing jobs near you
High Performance Computing (HPC) Engineer

High Performance Computing (HPC) Engineer

Federal Reserve Bank of San Francisco

Oklahoma City, OK

Full-time

Posted 18 days ago

Job description

CompanyFederal Reserve Bank of Kansas CityWhen you join the Federal Reserve-the nation's central bank-you'll play a key role, collaborating with leading tech professionals to strengthen and protect our economic, financial and payments systems. We invest in contemporary and emerging technology each year to support the Federal Reserve and our economy, and we're building a dynamic and diverse team for our future.

Important Information

  • Open to US Citizens, Green Card holders or Permanent Residents with at least 3 years of residency, with the intent to become a US citizen.

  • No sponsorship is available. Candidates must have valid work authorization, without an end date, to be considered.

  • This position requires working on-site, in Kansas City, Denver, Oklahoma City or Omaha, with 5 days per month work from home flexibility. Relocation assistance is available.

About the Role

The Center for the Advancement of Data and Research in Economics (CADRE) supports data and computationally intensive research and analytics for staff in the Economic Research division of the Federal Reserve Bank of Kansas City and across the Federal Reserve System. Our services include multiple high performance computing environments, research data warehousing, and advanced analytical tools. We are an embedded technology team within the division of Economic Research, Regional, and Community Affairs.

We are seeking an experienced High Performance Computing Engineer who can plan, implement, and maintain advanced cyberinfrastructure solutions. The ideal candidate will have deep expertise in HPC architectures, parallel computing frameworks, and scientific computing applications. You will work independently while collaborating with researchers to solve complex computational challenges that support critical economic research initiatives.

Key Activities

Operations

  • Design, deploy, configure, and administer medium scale HPC clusters and associated storage systems.

  • Monitor system health, performance metrics, and resource utilization to ensure optimal operation.

  • Implement robust security protocols and perform regular maintenance including upgrades and patching.

  • Troubleshoot complex hardware and software issues in a multi-user research environment.

  • Manage job scheduling and workload optimization using tools like SLURM.

  • Administer parallel file systems (such as ceph and IBM Spectrum Scale/GPFS) and storage solutions.

Development

  • Design and implement innovative HPC solutions to address evolving research requirements.

  • Create and maintain automation scripts and tools to streamline system administration.

  • Optimize scientific applications and computational workflows for performance.

  • Implement container technologies (Docker, Singularity) for reproducible research.

  • Support GPU computing and accelerator technologies for specialized workloads.

  • Define and track performance metrics to ensure efficient current and future use of resources.

Partnership/Collaboration

  • Partner closely with researchers to understand computational needs and translate them into technical solutions.

  • Collaborate with network, security, and data center teams to ensure integrated operations.

  • Build and maintain relationships with external vendors and technology partners.

  • Participate in the HPC community to stay current with emerging technologies and best practices.

  • Serve as a technical advisor on infrastructure planning and technology roadmaps.

Documentation/Training

  • Develop comprehensive documentation for systems, policies, and procedures.

  • Create user guides and training materials for researchers utilizing HPC resources.

  • Provide mentorship to junior staff and knowledge sharing across teams.

  • Conduct workshops and training sessions on effective use of HPC resources.

Qualifications

Required

  • Bachelor's degree in computer science, engineering, mathematics, or related field, or equivalent combination of education and experience.

  • Minimum of 6 years of relevant experience in HPC administration and systems engineering.

  • Extensive experience with Linux operating systems (Red Hat/CentOS) in an HPC environment.

  • Strong command line skills and proficiency in scripting languages (Python, Bash).

  • Experience with job scheduling systems (SLURM, PBS, LSF) and resource management.

  • Knowledge of parallel file systems and storage technologies (e.g. ceph, GPFS, Lustre, BeeGFS).

  • Familiarity with parallel programming models (MPI, OpenMP) and scientific computing frameworks.

  • Experience with configuration management and automation tools (Salt, Ansible, Puppet).

  • Demonstrated problem-solving abilities and analytical thinking.

Preferred

  • Advanced degree in a computational field.

  • Experience with cloud computing platforms and hybrid HPC environments.

  • Experience with GitLab CI/CD pipelines for research software development.

  • Understanding of GPU computing and accelerator technologies (CUDA, OpenACC).

  • Experience supporting machine learning and AI workloads on HPC systems.

Additional Information

How We Work (HWW)

  • On-site: 5 days per month remote work flexibility

  • Location: Kansas City, Denver, Oklahoma City, or Omaha

  • Remote Eligible: No

  • Relocation Assistance: Yes

Salary

  • $110,300 - $155,700 / Senior Level

  • $125,200 - $176,700 / Advanced Level

  • $139,500 - $196,800 / Expert-Lead Level

  • Final offers are determined by factors including the candidate's qualifications, internal alignment considerations, district assignment, and geographic location.

Screening: US Citizens and Green Card holders or Permanent Residents with at least 3 years of residency, with the intent to become a US citizen. This position has additional screening requirements due to the information accessed while performing the job. These additional screenings would be initiated at the time of offer acceptance and could take up to a couple of months to be completed. You can begin work before the screening is completed; however, continued employment is contingent on acceptable screening results. The areas screened may include education/employment verification, criminal history, credit history, and reference checks.

Sponsorship: The Federal Reserve Bank of Kansas City will not sponsor a new applicant for employment authorization for this position. Applicants must be currently authorized to work in the United States without the need for visa sponsorship now or in the future.

About Us

  • Total Rewards & Benefits

  • Who We Are

  • What We Do

Follow us on LinkedIn, Instagram, X (formerly Twitter), and YouTube #KCFedIT

Full Time / Part TimeFull timeRegular / TemporaryRegularJob Exempt (Yes / No)YesJob CategoryInformation Technology Family GroupWork ShiftFirst (United States of America)

The Federal Reserve Banks are committed to equal employment opportunity for employees and job applicants in compliance with applicable law and to an environment where employees are valued for their differences.

Always verify and apply to jobs on Federal Reserve System Careers (https://rb.wd5.myworkdayjobs.com/FRS) or through verified Federal Reserve Bank social media channels.

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