ZipRecruiter

Log In

1

Machine Learning Quantum Computing Jobs in North Carolina

Duke University

Postdoctoral Associate

Durham, NC · On-site

Familiarity with machine learning applications in medical imaging. * Experience working with hardware-software integration and custom instrumentation. * Knowledge of research computing, image ...

Duke University

Postdoctoral Associate

Durham, NC · On-site

Familiarity with machine learning applications in medical imaging. * Experience working with hardware-software integration and custom instrumentation. * Knowledge of research computing, image ...

Duke University

Associate in Research

Durham, NC · On-site

You will help design and implement machine learning models, maintain computational pipelines, and analyze complex biological datasets using high-performance computing environments. This position ...

Duke University

Associate in Research

Durham, NC · On-site

You will help design and implement machine learning models, maintain computational pipelines, and analyze complex biological datasets using high-performance computing environments. This position ...

IBM

$18.25 - $23.75/hr

At IBM, we pride ourselves on being an early adopter of artificial intelligence, quantum computing ... Machines Corporation Shift General (daytime) Is this role a commissionable/sales incentive based ...

LexisNexis Risk Solutions

Lead Data Scientist

Raleigh, NC · On-site

$104.90 - $174.70/hr

The ideal candidate will have a deep understanding of machine learning algorithms, experience ... Experience working with large datasets and distributed computing systems (e.g., Hadoop, Spark)

previous page

Showing results 41-60

All JobsMachine Learning Quantum Computing JobsMachine Learning Quantum Computing Jobs in North Carolina

Machine Learning Quantum Computing information

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 are popular job titles related to Machine Learning Quantum Computing jobs in North Carolina?

For Machine Learning Quantum Computing jobs in North Carolina, the most frequently searched job titles are:

What job categories do people searching Machine Learning Quantum Computing jobs in North Carolina look for?

The top searched job categories for Machine Learning Quantum Computing jobs in North Carolina are:

What cities in North Carolina are hiring for Machine Learning Quantum Computing jobs?

Cities in North Carolina with the most Machine Learning Quantum Computing job openings:

Machine Learning Quantum Computing jobs near you

Need AI/ML Data Science Lead contract jobs at Cary, NC

Tech Mirrors

Cary, NC • On-site

$120 - $180/hr

Other

Posted 18 days ago

Job description

Job Title: AI/ML Data Science Lead

Location: Cary, NC (Need locals)

Duration: Contract

Key Responsibilities
  • Team Leadership: Lead the solution and a team of data scientists delivering AI and ML solution for marketing and business engagement use cases
  • Ownership: Accountability for technical decisions, project outcomes, timelines, and production stability within a defined domain.
  • Planning and Business alignment: Lead the planning and execution of data science use cases, ensuring alignment with business goals and objectives.
  • Model Development: Design, train, and optimize machine learning and deep learning models for a variety of marketing and business engagement use cases
  • Data Analysis: Analyze complex data sets to identify trends, patterns, and actionable insights that can inform business strategies.
  • Collaboration: Collaborate with stakeholders and cross-functional teams to develop and implement data-driven solutions.
  • Platform Integration: Enable seamless integration of AI capabilities into business applications and workflows through APIs, SDKs, and microservices.
  • Stakeholder Communication: Visualize data, create reports, and present findings to senior management and cross-functional teams.
  • Develop statistical models, analytics, and Machine Learning algorithms using Python and cloud tools (Azure).
  • Research and Innovation: Stay up to date with the latest advances in AI, Data Science, and Machine Learning.
  • ML-Ops Best Practices: Optimize platform components for efficiency, scalability, and reliability using best practices in distributed computing, resource management, and cloud-native architectures.
Essential Business Experience and Technical Skills Required
  • Bachelor’s or master’s degree in computer science, Data Science, Engineering, Mathematics, or a related field.
  • 8+ years of overall experience in AI/ML engineering and/or data science.
  • 5+ years of insurance business and/or financial industry experience with sales, marketing, and/or customer engagement analytics.
  • Proven experience designing, deploying, and operating production ML and/ or GenAI solutions, including APIs, batch, and real-time inference.
  • Experience in developing Machine Learning models using Python (preferably in the cloud)
  • Familiarity with best practices for responsible AI, including data privacy, bias mitigation, and/or model monitoring.
  • Strong SQL knowledge and data analysis skills for data anomaly detection and Exploratory Data Analysis.
  • Experience with Dominos, Power BI, and/or Azure ML
  • Statistical Knowledge: A strong understanding of statistics and mathematics is essential for data analysis and prediction.
  • Use predictive modeling or AI solutions to increase and optimize customer experience/communication, revenue generation, ad targeting, and other business outcomes
  • Very good presentation skills to present results clearly and effectively by creating presentations with storytelling, visualizations & results
  • Very good problem solver and excellent communication skills – both written and verbal
#J-18808-Ljbffr

Apply