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Machine Learning Quantum Computing Jobs in Altamonte Springs, FL

Linear Algebra Tutor

Orlando, FL · Remote

$18 - $40/hr

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

Conduct advanced computational chemistry research with a focus on nanophotonics, quantum mechanics, and machine learning-assisted modeling and simulations. * Prepare manuscripts and conference ...

Python Tutor

Orlando, FL · 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 ...

... quantum and energy applications, prediction of materials synthesizability, defect physics in ... Python coding and machine learning skills. Additional Application Materials Required: Special ...

... machine learning, and data science. The successful candidate will work with Dr. Yohanna Mejia Cruz ... Strong programming skills in Python, including experience with scientific computing and data ...

... machine learning and AI workloads. The goal is to advance UCF researchers' science by providing tools, training, support, and services, such as high-performance computing, high-throughput computing ...

... machine learning research applications. * Curriculum Awareness & Adaptive Instruction: Familiar ... Adapts instruction using R or Python statistical computing, research paper examples, and proof ...

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Machine Learning Quantum Computing information

See Altamonte Springs, FL salary details

$23.8K

$39.8K

$82.3K

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

As of Aug 30, 2026, the average yearly pay for machine learning quantum computing in Altamonte Springs, FL is $39,806.00, according to ZipRecruiter salary data. Most workers in this role earn between $30,400.00 and $43,000.00 per year, depending on experience, location, and employer.

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 are the key skills and qualifications needed to thrive as a machine learning quantum computing specialist?

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 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 cities near Altamonte Springs, FL are hiring for Machine Learning Quantum Computing jobs?

Cities near Altamonte Springs, FL with the most Machine Learning Quantum Computing job openings:

Senior Materials Expert - AI‑Driven Materials Discovery

Siemens Energy, Inc.

Orlando, FL • On-site

Full-time

Medical, Retirement, PTO

Re-posted 22 hours ago


Siemens Energy rating

8.3

Company rating: 8.3 out of 10

Based on 88 frontline employees who took The Breakroom Quiz

118th of 495 rated machine equipment manufacturers


Job description

A Snapshot of Your Day
As a Senior Materials Expert - AI-Driven Materials Discovery, you will lead the next generation of industrial materials innovation by leveraging artificial intelligence, advanced simulation, and emerging computing technologies to accelerate materials discovery and optimization across Siemens Energy's value chain. You will bridge materials science expertise with digital technologies by developing AI-driven workflows, computational models, and materials data platforms that reduce development time, improve performance, and enable scalable industrial solutions. Working across R&D, Engineering, IT, and business functions, you will lead interdisciplinary teams, drive strategic innovation initiatives, and translate scientific advancements into impactful applications and intellectual property.
How You'll Make an Impact
  • Lead the development and execution of AI-driven materials discovery strategies by designing machine learning models, computational simulations, and digital materials twins to predict material properties and accelerate innovation cycles
  • Develop and integrate advanced computational workflows, including AI/ML models, multi-scale simulations, density functional theory (DFT), molecular dynamics (MD), finite element modeling (FEM), and emerging quantum computing approaches to enable next-generation materials development
  • Build and manage materials data ecosystems by establishing data pipelines, supporting FAIR data standards, curating materials databases, and integrating experimental and computational datasets to improve data-driven decision-making
  • Conduct advanced materials research focused on structure-property-process relationships, including material selection, composites, polymers, alloys, metallurgy, characterization, testing, and failure analysis to support industrial applications
  • Lead interdisciplinary R&D programs by managing technical roadmaps, project milestones, research reviews, external partnerships, and collaboration across global teams, scientific networks, and innovation communities
  • Drive process innovation and knowledge development by mentoring scientists and engineers, establishing new research methodologies, communicating technical findings to leadership, and translating scientific results into scalable business solutions and intellectual property

What You Bring
  • Ph.D. or Master's degree in Materials Science, Chemical Engineering, Physics, Computer Science, Engineering, or a related technical field with a focus on computational materials science or a comparable discipline
  • 8+ years of experience leading research, engineering, or technology development projects in materials science, computational modeling, AI-driven innovation, or industrial R&D environments
  • Deep expertise in computational materials science, materials informatics, machine learning, data science, and simulation methods, with demonstrated experience applying AI/ML techniques such as neural networks, Bayesian optimization, generative models, or graph neural networks (GNNs)
  • Strong experience with materials modeling, experimental-computational integration, HPC environments, large-scale data processing, and advanced simulation techniques; knowledge of quantum computing concepts and algorithms for materials modeling preferred
  • Proven ability to lead cross-functional and matrix teams, influence stakeholders, manage complex technical programs, and translate scientific research into practical industrial applications
  • Excellent analytical, problem-solving, communication, and strategic thinking skills with the ability to collaborate effectively in a global, flexible, and innovation-focused environment; advanced English proficiency required, German language skills beneficial

Who is Siemens Energy?
At Siemens Energy, we are more than just an energy technology company. With ~100,000 dedicated employees in more than 90 countries, we develop the energy systems of the future, ensuring that the growing energy demand of the global community is met reliably and sustainably. The technologies created in our research departments and factories drive the energy transition and provide the base for one sixth of the world's electricity generation.
Our global team is committed to making sustainable, reliable, and affordable energy a reality by pushing the boundaries of what is possible. We uphold a 150-year legacy of innovation that encourages our search for people who will support our focus on decarbonization, new technologies, and energy transformation.
Find out how you can make a difference at Siemens Energy: h ttps://www.siemens-energy.com/employeevideo
Rewards
  • Career growth and development opportunities; supportive work culture
  • Company paid Health and wellness benefits
  • Paid Time Off and paid holidays
  • 401K savings plan with company match
  • Family building benefits
  • Parental leave

https://jobs.siemens-energy.com/jobs
Equal Employment Opportunity Statement
Siemens Energy and Siemens Gamesa Renewable Energy is an Equal Opportunity and Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to their race, color, creed, religion, national origin, citizenship status, ancestry, sex, age, physical or mental disability unrelated to ability, marital status, family responsibilities, pregnancy, genetic information, sexual orientation, gender expression, gender identity, transgender, sex stereotyping, order of protection status, protected veteran or military status, or an unfavorable discharge from military service, and other categories protected by federal, state or local law.
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