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Machine Learning Quantum Computing Jobs in Texas

Machine Learning Operations Engineer Category: Software Development/ Engineering Main location ... Deep understanding of the Hadoop ecosystem, distributed computing, and performance tuning.

Senior Machine Learning Engineer

Austin, TX

$103K - $142K/yr

Senior Machine Learning Engineer We are seeking a Senior Machine Learning Engineer to support our ... Strong understanding of GPU computing, CUDA, and performance profiling. We at webAI are committed ...

Machine Learning Operations Engineer

Dallas, TX · On-site

$113K - $136K/yr

... machine learning models in production environments. Desired candidate will work closely with ... Deep understanding of the Hadoop ecosystem, distributed computing, and performance tuning.

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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:
Machine Learning Operations Engineer

Machine Learning Operations Engineer

CGI

Dallas, TX

$113K - $136K/yr

Other

Retirement, PTO

Posted 24 days ago


CGI rating

7.2

Company rating: 7.2 out of 10

Based on 18 frontline employees who took The Breakroom Quiz

112th of 204 rated it services


Job description

Machine Learning Operations Engineer
Category: Software Development/ Engineering
Main location: United States, Texas, Dallas
Alternate Location(s): United States, Strongsville
United States, Pittsburgh
Position ID:J0426-1279
Employment Type: Full Time
Position Description:
We are seeking an experienced MLOps Engineer with strong expertise in Python and big data technologies to join our team. This role focuses on operational excellence, including optimizing feature engineering pipelines and maintaining machine learning models in production environments. Desired candidate will work closely with platform and data science teams to ensure scalable, reliable, and high-performance ML workflows using existing frameworks.
This position will be performed onsite five days a week from any our client sites in Dallas, t/Strongsville, OH/Pittsburg, PA
Future duties and responsibilities
. Optimize and maintain large-scale feature engineering pipelines using PySpark, Pandas, and PyArrow on Hadoop-based infrastructure.
. Refactor and modularize ML codebases to enhance reusability, maintainability, and performance.
. Collaborate with platform teams on compute capacity planning, resource allocation, and system upgrades.
. Integrate with existing model serving frameworks to support testing, deployment, and rollback processes.
. Monitor and troubleshoot production ML pipelines, ensuring high reliability, low latency, and cost efficiency.
. Contribute to internal ML platforms by sharing insights, proposing improvements, and documenting best practices.
. Build near real-time ML pipelines using Kafka and Spark Streaming.
. Work with AWS and SageMaker MLOps ecosystem.
Required qualifications to be successful in this role
. 6+ years of experience in software engineering, data engineering, or MLOps roles.
. Strong programming expertise in Python, with hands-on experience in Pandas, PySpark, and PyArrow.
. Deep understanding of the Hadoop ecosystem, distributed computing, and performance tuning.
. Experience with CI/CD pipelines and best practices in ML environments.
. Hands-on experience with monitoring tools for ML pipeline health and performance.
. Strong collaboration skills with experience working in cross-functional teams (platform, data science, engineering).
. Experience contributing to or building internal MLOps frameworks/platforms.
. Familiarity with SLURM clusters or other distributed job schedulers.
. Exposure to Kafka, Spark Streaming, or other real-time data processing technologies.
. Understanding of ML lifecycle management, including versioning, deployment, and drift detection.
#2026NS
#LI-SG2
#DICE
Other Information:
CGI is required by law in some jurisdictions to include a reasonable estimate of the compensation range for this role. The determination of this range includes various factors not limited to skill set, level, experience, relevant training, and licensure and certifications. To support the ability to reward for merit-based performance, CGI typically does not hire individuals at or near the top of the range for their role. Compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range for this role in the U.S. is $62,900.00 - $139,300.00.
CGI's benefits are offered to eligible professionals on their first day of employment to include:
. Competitive compensation
. Comprehensive insurance options
. Matching contributions through the 401(k) plan and the share purchase plan
. Paid time off for vacation, holidays, and sick time
. Paid parental leave
.Learning opportunities and tuition assistance
. Wellness and Well-being programs
Skills:
  • Amazon Web Services Cloud
  • Apache Hadoop YARN
  • Apache Kafka
  • AWS SageMaker
  • Big Data,Analytics&Operations
  • Hadoop Hive
  • Machine Learning
  • Pandas
  • Python

What you can expect from us:
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Qualified applicants will receive consideration for employment without regard to their race, ethnicity, ancestry, color, sex, religion, creed, age, national origin, citizenship status, disability, pregnancy, medical condition, military and veteran status, marital status, sexual orientation or perceived sexual orientation, gender, gender identity, and gender expression, familial status or responsibilities, reproductive health decisions, political affiliation, genetic information, height, weight, or any other legally protected status or characteristics to the extent required by applicable federal, state, and/or local laws where we do business.
CGI provides reasonable accommodations to qualified individuals with disabilities. If you need an accommodation to apply for a job in the U.S., please email the CGI U.S. Employment Compliance mailbox at US_Employment_Compliance@cgi.com. You will need to reference the Position ID of the position in which you are interested. Your message will be routed to the appropriate recruiter who will assist you. Please note, this email address is only to be used for those individuals who need an accommodation to apply for a job. Emails for any other reason or those that do not include a Position ID will not be returned.
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All CGI offers of employment in the U.S. are contingent upon the ability to successfully complete a background investigation. Background investigation components can vary dependent upon specific assignment and/or level of US government security clearance held. Dependent upon role and/or federal government security clearance requirements, and in accordance with applicable laws, some background investigations may include a credit check. CGI will consider for employment qualified applicants with arrests and conviction records in accordance with all local regulations and ordinances.
CGI will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with CGI's legal duty to furnish information.

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