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Quantum Machine Learning Jobs in Texas (NOW HIRING)

Emphasizes geometric interpretation of transformations and connects linear algebra to computer graphics, machine learning, and quantum mechanics applications. * Curriculum Awareness & Adaptive ...

Emphasizes geometric interpretation of transformations and connects linear algebra to computer graphics, machine learning, and quantum mechanics applications. * Curriculum Awareness & Adaptive ...

Emphasizes geometric interpretation of transformations and connects linear algebra to computer graphics, machine learning, and quantum mechanics applications. * Curriculum Awareness & Adaptive ...

Emphasizes geometric interpretation of transformations and connects linear algebra to computer graphics, machine learning, and quantum mechanics applications. * Curriculum Awareness & Adaptive ...

Emphasizes geometric interpretation of transformations and connects linear algebra to computer graphics, machine learning, and quantum mechanics applications. * Curriculum Awareness & Adaptive ...

Emphasizes geometric interpretation of transformations and connects linear algebra to computer graphics, machine learning, and quantum mechanics applications. * Curriculum Awareness & Adaptive ...

Emphasizes geometric interpretation of transformations and connects linear algebra to computer graphics, machine learning, and quantum mechanics applications. * Curriculum Awareness & Adaptive ...

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Quantum Machine Learning information

See Texas salary details

$23.8K

$39.7K

$82K

How much do quantum machine learning jobs pay per year?

As of Jun 9, 2026, the average yearly pay for quantum machine learning in Texas is $39,673.00, according to ZipRecruiter salary data. Most workers in this role earn between $30,300.00 and $42,900.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Quantum Machine Learning position, and why are they important?

To thrive in Quantum Machine Learning, you need a solid background in quantum physics, machine learning, linear algebra, and programming—often supported by a graduate degree in a related field. Familiarity with quantum computing frameworks such as Qiskit or Cirq, and experience with conventional ML libraries like TensorFlow or PyTorch are typically expected. Strong problem-solving abilities, effective communication, and a collaborative mindset help professionals stand out. Mastery of these skills and qualities is essential for tackling complex interdisciplinary challenges and driving innovation in this rapidly evolving field.

What types of projects or problems does a Quantum Machine Learning professional typically work on?

Quantum Machine Learning professionals often work on exploratory projects at the intersection of quantum computing and artificial intelligence, such as developing new algorithms that leverage quantum hardware for faster data processing or optimizing classical ML models using quantum techniques. Daily tasks may include designing experiments, simulating quantum systems, analyzing results, and collaborating with physicists and software engineers. The work can range from foundational research to applied development, depending on the organization's focus. These roles frequently involve teamwork and staying updated on emerging academic and industry advances to ensure innovative problem-solving approaches.

What is a Quantum Machine Learning job?

A Quantum Machine Learning (QML) job involves applying principles of quantum computing to machine learning tasks. Professionals in this field develop algorithms that leverage quantum systems to improve computational efficiency and solve complex problems faster than classical methods. Responsibilities often include researching quantum algorithms, implementing quantum circuits, and working with tools like Qiskit or TensorFlow Quantum. These roles are typically found in research labs, tech companies, and startups exploring the intersection of AI and quantum technology. Strong backgrounds in quantum mechanics, linear algebra, and computer science are essential.

What cities in Texas are hiring for Quantum Machine Learning jobs? Cities in Texas with the most Quantum Machine Learning job openings:
Infographic showing various Quantum Machine Learning job openings in Texas as of May 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $39,673 per year, or $19.1 per hour.

Quantum Software Engineer (US)

Zapata Quantum

Zapata, TX • On-site

Full-time

Posted 18 days ago


Job description

About the role
We are seeking a Quantum Software Engineer to build AI-powered tools that massively accelerate how quantum applications are designed and resource-estimated. You will fuse modern AI-LLMs, coding agents, and ML-based heuristics-with quantum circuit construction, compilation, and analysis, compressing workflows that currently take weeks of expert effort into hours. Your tooling will directly shape Zapata's ability to evaluate and deliver quantum solutions across cryptography, pharmaceuticals, finance, materials discovery, and defense.
This position offers a high level of individual ownership and is well-suited to engineers who are excited to push the frontier of AI-assisted scientific software within a small, focused team. You will partner closely with algorithm scientists and customers to understand their design and resource-estimation workflows, then build tools that turn those workflows into automated, scalable pipelines. This position is classified as exempt under applicable wage and hour laws.
What you'll do
  • Design and build AI-powered tools that accelerate quantum application design-from problem intake through algorithm selection, circuit construction, and validation
  • Develop automated resource estimation pipelines that use LLMs and ML models to rapidly predict qubit counts, gate counts, and runtime for candidate quantum solutions
  • Build agentic workflows that orchestrate quantum SDKs, compilation passes, simulators, and analysis tools
  • Integrate state-of-the-art AI coding assistants and LLM APIs directly into internal scientific tooling to compress expert-led workflows into automated pipelines
  • Benchmark and continuously improve the accuracy, speed, and reliability of AI-driven tooling against expert-curated baselines
  • Collaborate closely with quantum algorithm scientists to capture their reasoning and encode it into reusable AI-driven tools
  • Deliver high-quality software with minimal supervision, demonstrating autonomy in execution and technical decision-making

Qualifications
  • Strong software engineering fundamentals, including testing, code review, and CI/CD practices
  • BS or MS in Computer Science, Physics, Engineering, or a related field, or equivalent professional experience
  • Demonstrated experience shipping software that leverages LLMs, AI agents, or other machine learning components
  • Proficient programming skills in Python, with working knowledge of modern LLM APIs (Anthropic, OpenAI, or equivalent) and tool-use / function-calling patterns
  • Deep familiarity with AI-assisted development workflows (Claude Code, Cursor, or similar) and a drive to use them to massively accelerate your own output and that of the team
  • Familiarity with quantum computing concepts and a willingness to learn quantum algorithms and resource estimation in depth
  • Ability to work independently and manage deliverables with minimal oversight
  • Strong judgment about when to apply AI and when not to
  • A commitment to measuring tool quality against expert baselines

Desired Programming Skills
  • Python - for tooling, scientific code, and LLM-powered applications
  • LLM APIs and tool-use / function-calling patterns (Anthropic, OpenAI, or similar)
  • Agent frameworks and orchestration (LangGraph, pydantic-ai, or custom harnesses)
  • Quantum SDKs (Qiskit, Cirq, PennyLane, or similar) for scripting design and estimation workflows
  • AI-assisted development (e.g., Claude Code)
  • Git and modern CI/CD tooling
  • Evals and benchmark design for AI systems
  • Software testing frameworks (pytest, hypothesis)
  • NumPy, SciPy, and the scientific Python stack
  • Retrieval-augmented generation and vector databases
  • Containerization (Docker) and cloud infrastructure (AWS, Azure, or GCP)
  • Prompt Engineering

Preferred Experience
  • Demonstrated experience shipping software that leverages LLMs, AI agents, or other machine learning components
  • Experience building developer tools, scientific workflows, or research automation that leverages AI to speed up expert work
  • Strong communication skills and comfort collaborating across research and engineering teams

About Zapata Quantum
Zapata Quantum is shaping the future of quantum computing: setting the standards for what's viable, valuable, and worth building. The Company powers quantum applications across cryptography, pharmaceuticals, finance, materials discovery, defense, and beyond, translating cutting-edge research into real-world impact.
Zapata is the only organization to have contributed across every technical area of DARPA's Quantum Benchmarking program, giving it a uniquely comprehensive view of what it takes to make quantum computing work in practice. Now restructured and sharply focused, Zapata Quantum stands alone as the only publicly traded, pure-play quantum software company fully dedicated to unlocking quantum's commercial potential.
We're rebuilding at a pivotal moment for the industry-bringing together a team that will help define how quantum delivers value in the real world, with the opportunity for meaningful ownership as we shape the commercial path forward.