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Machine Learning Quantum Computing Jobs in Texas

Q2

Machine Learning Engineer

Austin, TX

SUMMARY The Machine Learning Engineer provides hands-on expertise in designing, implementing, and ... computing resources Strong analytical, problem-solving, and collaboration skills This position ...

Cymertek

Machine Learning Engineer

San Antonio, TX

Machine Learning Engineer LOCATIONSan Antonio, TX 78208 CLEARANCETS/SCI Full Poly (Please note this ... Knowledge of edge computing and model optimization for deployment PLUG IN to CYMERTEK - And design ...

Cymertek

Machine Learning Engineer

San Antonio, TX · On-site

Machine Learning Engineer LOCATION San Antonio, TX 78208 CLEARANCE TS/SCI Full Poly (Please note ... Knowledge of edge computing and model optimization for deployment PLUG IN to CYMERTEK - And design ...

Ascentt

Senior Machine Learning Engineer

Plano, TX · On-site

$100K - $137.30K/yr

Analyze large datasets using PySpark and other distributed computing frameworks to extract insights and prepare features for ML pipelines. * Apply a wide range of statistical, machine learning, and ...

Ascentt

Senior Machine Learning Engineer

Plano, TX · On-site

$100K - $137.30K/yr

Analyze large datasets using PySpark and other distributed computing frameworks to extract insights and prepare features for ML pipelines. * Apply a wide range of statistical, machine learning, and ...

Capital One

Senior Machine Learning Engineer

Plano, TX · On-site +1

$100K - $137.30K/yr

Senior Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part ... computing * At least 2 years of on-the-job experience with an industry recognized ML frameworks ...

Capital One

Lead Machine Learning Engineer

Plano, TX · On-site +1

$98.10K - $129.20K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... distributed computing (Internship experience does not apply) * At least 4 years of experience ...

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Machine Learning Quantum Computing information

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.

What are popular job titles related to Machine Learning Quantum Computing jobs in Texas? For Machine Learning Quantum Computing jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Machine Learning Quantum Computing jobs in Texas look for? The top searched job categories for Machine Learning Quantum Computing jobs in Texas are:
What cities in Texas are hiring for Machine Learning Quantum Computing jobs? Cities in Texas with the most Machine Learning Quantum Computing job openings:
Machine Learning Quantum Computing jobs near you

Quantum Software Engineer (non-US)

Zapata Quantum

Zapata, TX • On-site

Contractor

Posted 8 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.

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