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Machine Learning Quantum Computing Jobs in Texas

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 ...

Senior Machine Learning Engineer

Austin, TX

$121K - $160K/yr

We use Machine Learning, Reinforcement Learning, AI, Control and Optimization Systems, and Auction ... Ability to work with large scale computing frameworks, data analysis systems, and modelling ...

Senior Machine Learning Engineer

Plano, TX · On-site

$100K - $137K/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 ...

Senior Machine Learning Engineer

Plano, TX · On-site

$100K - $137K/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 ...

Lead Machine Learning Engineer

Plano, TX · On-site +1

$98K - $129K/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 ...

We are seeking an experienced Staff Machine Learning Engineer with a strong background in Large ... Experience with cloud computing services (AWS, Azure, GCP). * Knowledge of Big Data technologies ...

Staff Machine Learning Engineer

Austin, TX · Hybrid

$249K - $338K/yr

Job Overview: The mission of the Central Technology ML (CTML) team is to pioneer and implement the technology roadmap that paves the way for the future of machine learning computing on Arm ...

Staff Machine Learning Engineer

Austin, TX · On-site

$249K - $338K/yr

Job Overview: The mission of the Central Technology ML (CTML) team is to pioneer and implement the technology roadmap that paves the way for the future of machine learning computing on Arm ...

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Machine Learning Quantum Computing information

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 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 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:

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Posted 10 days ago


Job description

Mariana Minerals Job Posting

Mariana Minerals is a software-first, vertically integrated minerals company on a mission to supply the critical minerals powering modern energy, AI, and defense technologies. We're reimagining the minerals supply chain by combining deep industry expertise with advanced software, automation, and data-driven decision-making.

The Role

Mariana Minerals is building the critical minerals supply chain from the ground up—and we're looking for Machine Learning Engineers to help make it autonomous.

We're not a software company selling tools to mining operators. We are a mining company that builds software. Mariana designs, builds, commissions, and operates our own mines and refineries. We develop proprietary chemical processes and run them at lab, pilot, and commercial scale. Today, we're producing battery-grade lithium salts from real oil and gas wastewater in our facilities. Our first commercial-scale lithium production facility, Lithium One, is targeting initial production in Q1 of 2027.

As a Machine Learning Engineer at Mariana, you'll help build and improve the machine learning systems that control our mineral refining facilities. You'll start with well-scoped problems inside our simulators and training pipelines—and ramp quickly toward owning models that run on real, operating plants. Your work won't live behind dashboards or proxy metrics; you'll see its impact in real recovery rates, energy consumption, reagent usage, and uptime.

The Tech

This is some of the most interesting applied AI work happening today.

Our internal platform uses the same reinforcement learning toolkits that power self-driving vehicles and humanoid robots—but applied to autonomous, short-interval control of mineral refining circuits. Models adjust operating set points and configurations in real time, optimizing across lithium recovery, reagent consumption, energy intensity, and equipment uptime simultaneously.

The environment is noisy and non-stationary: wastewater compositions shift, ore grades change, equipment ages. The system must continuously adapt. The end goal is fully autonomous refining operations. When you ship here, you can literally watch the physics change.

Under the hood, that means training control models inside physically realistic simulators of our process units, then closing the gap against real plant data before anything touches live equipment.

What You'll Do
  • Run reinforcement learning experiments in our physically realistic simulators of mineral processing operations, and help turn the results into better controllers.

  • Build and refine pieces of our training environments—reward functions, observations, and action logic—with guidance from senior engineers.

  • Train control models, track and interpret their performance, and dig into why a model underperforms.

  • Help close the gap between simulation and reality by comparing model behavior against real plant data and flagging where the physics diverges.

  • Write clean, well-tested code and contribute to the services that put models into production.

  • Partner with process and chemistry experts to understand the unit operations you're modeling.

Desired Qualifications
  • 0–4 years of experience (including internships or research) in machine learning, reinforcement learning, or scientific computing—or a strong recent graduate with demonstrated project depth.

  • Solid grounding in machine learning fundamentals, with working knowledge of modern deep learning; exposure to reinforcement learning is a strong plus.

  • Proficiency in Python and comfort reading and debugging an existing codebase.

  • Curiosity about physical, industrial systems and eagerness to learn chemistry and process engineering from experts who will challenge your assumptions.

  • A self-starter who asks good questions, ships, and escalates blockers early.

Why This Role

We own the projects, generate the data, and close the loop. Every facility we build makes the software smarter—and the next facility faster and cheaper.

Mining is one of the last major industrial sectors that hasn't been rebuilt with modern software. The opportunity here isn't a feature gap—it's entire workflows and systems that don't exist yet.

Your work will directly shape how critical minerals are produced at scale in the coming decades.

Why Join Us?

At Mariana Minerals, you'll be part of a mission-driven team reshaping the way critical minerals are sourced and supplied globally. You'll have the autonomy to make big decisions, the tool

Our culture is built on three principles:

  • Extreme Ownership – We take full responsibility for outcomes, relentlessly driving toward solutions.

  • Engineer Out Requirements, then Automate – We simplify, optimize, and then automate for scale.

  • Share Your Legos – We collaborate openly, share knowledge, and empower each other to build bigger, better solutions.

Join us as we build the future of responsible mineral sourcing and supply.

Mariana is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected status.