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Internship Ibm Quantum Machine Learning Jobs (NOW HIRING)

Jane Street

Machine Learning Engineer

New York, NY

Many classes and activities are shared with our Software Engineering interns, while others focus specifically on machine learning applications and techniques. Machine learning is a critical pillar of ...

Jane Street

Machine Learning Engineer

New York, NY · On-site

Many classes and activities are shared with our Software Engineering interns, while others focus specifically on machine learning applications and techniques. Machine learning is a critical pillar of ...

Visa

Staff Research Scientist

Foster City, CA · On-site

$169K/yr

... quantum machine learning, distributed quantum computing and/or quantum security and privacy with ... Mentor interns and contribute to a collaborative research environment. This is a hybrid position.

QCi

Senior Engineer, Quantum Algorithms

Hoboken, NJ · On-site

Design and implement novel algorithms that map optimization and machine-learning problems onto entropy-based photonic quantum processors, including post-processing pipelines. * Build software layers ...

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How much do internship ibm quantum machine learning jobs pay per year?

As of Aug 6, 2026, the average yearly pay for internship ibm quantum machine learning in the United States is $42,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 per year, depending on experience, location, and employer.

What is an IBM Quantum Machine Learning internship?

An IBM Quantum Machine Learning Internship is a temporary position for students or recent graduates to work alongside IBM researchers and engineers on projects at the intersection of quantum computing and machine learning. Interns typically contribute to developing algorithms, running experiments on real quantum hardware, and advancing the understanding of how quantum computers can enhance machine learning tasks. The internship provides hands-on experience with IBM's quantum technologies, including Qiskit, and offers opportunities to collaborate with leading experts in the field. Applicants generally need a background in computer science, physics, mathematics, or related fields, and some familiarity with quantum computing concepts.

What is the difference between Internship Ibm Quantum Machine Learning vs Data Science Intern?

AspectInternship Ibm Quantum Machine LearningData Science Intern
Required CredentialsBasic knowledge of quantum computing, programming, and machine learningBackground in statistics, programming, and data analysis
Work EnvironmentResearch-focused, technology-driven, often in labs or R&D teamsBusiness or research settings, analyzing large datasets
Industry UsageEmerging field within tech and research sectorsWidely used across industries like finance, healthcare, and tech
Search & Comparison IntentUnderstanding quantum ML internship opportunitiesExploring data science internship roles

Internship Ibm Quantum Machine Learning focuses on applying quantum computing techniques to machine learning problems, often requiring knowledge of quantum algorithms and programming. In contrast, Data Science Internships involve analyzing data, building models, and deriving insights using traditional data analysis tools. Both roles are research-oriented but differ in technical focus and industry application.

What kinds of projects or tasks can interns expect to work on during an IBM Quantum Machine Learning internship?

During an IBM Quantum Machine Learning internship, interns often collaborate with research scientists and engineers on projects that explore the intersection of quantum computing and machine learning. Typical responsibilities include implementing quantum algorithms, analyzing experimental data, developing proof-of-concept applications, and contributing to open-source software or research publications. Interns may also participate in team meetings, technical discussions, and code reviews, gaining exposure to cutting-edge quantum technologies and professional research environments. This hands-on experience provides valuable insight into both academic and industry applications of quantum machine learning.

What are the key skills and qualifications needed to thrive as an IBM Quantum Machine Learning intern?

To excel as an IBM Quantum Machine Learning Intern, you typically need a background in computer science, physics, or a related field, with strong programming skills (Python) and foundational knowledge in quantum computing and machine learning. Familiarity with quantum programming frameworks such as Qiskit, as well as experience with machine learning libraries like TensorFlow or PyTorch, is highly beneficial. Strong analytical thinking, problem-solving abilities, and effective communication skills distinguish top candidates in this role. These competencies enable interns to contribute meaningfully to research projects, collaborate with interdisciplinary teams, and adapt to rapidly evolving technologies in quantum computing.
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Internship Ibm Quantum Machine Learning jobs near you
Infographic showing various Internship Ibm Quantum Machine Learning job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 24% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.

Data Science Machine Learning Internship (Summer 2027)

Castleton Commodities International LLC

Houston, TX

Full-time

Posted 16 days ago

Job description

Application Deadline: September 1, 11:59pm EST

Program Summary - Commercial Technology Internships

Company Overview:

Castleton Commodities International is a leading global energy commodities merchant and infrastructure asset investor. As a trader, CCI deploys capital on a proprietary basis in the physical and financial commodity markets, providing the Company with market insights and access. As a strategic investor and developer, CCI leverages its market expertise, operations capabilities, and industry knowledge to invest in, and develop, select commodity infrastructure assets. Our strategically integrated platform has generated strong risk-adjusted returns for our investors since our formation.

Position Overview:

CCI is developing a leading-edge Data Science platform, as staying at the forefront of data management and analytics is essential to our investment strategy. We are looking for motivated and detail-oriented Machine Learning Interns with a strong interest in quantitative analysis, particularly time series forecasting to join our Global Data Science team in Stamford, CT, Houston, TX, or New York City offices. Our Machine Learning Internship provides a unique opportunity to work with fundamental market data, generating insights that support our commercial trading business. You will be responsible for analyzing time series data related to market fundamentals in the Power, Natural Gas, and Oil sectors, helping to identify key supply and demand drivers. These insights will play a vital role in forecasting price movements and supporting risk management decisions.

Responsibilities:

  • Apply mathematical and statistical knowledge to enhance existing machine learning applications and explore new solutions.
  • Work closely with Data Scientists, Analysts, and Traders to design, implement, and optimize machine learning models for time series forecasting, including ARIMA/SARIMA, gradient boosting methods (e.g., XGBoost), LSTM networks, and linear regression-based approaches.
  • Assist in designing and implementing end-to-end data ingestion processes, ensuring seamless data flow to investing teams.
  • Work with desk heads, traders, and analysts to understand current data architecture, investment processes, and functional requirements for data science analysis.
  • Contribute to identifying and back-testing new data sets, leveraging machine learning techniques to drive insights.
  • Conduct ad hoc research on emerging project topics, including energy fundamental data, analytics trends, and best practices in big data and artificial intelligence.

Qualifications:

  • Currently pursuing a Bachelor's Degree or higher in Mathematics, Statistics, Physics, Computer Science or related technical field with a focus in Machine Learning.
  • Expected graduation date of Winter 2027 or Spring/Summer 2028.
  • Experience applying machine learning techniques such as regression, time series forecasting, deep learning, reinforcement learning, or predictive modeling to solve problems involving complex data patterns and market dynamics.
  • Strong programming experience in Python (preferred libraries: Pandas, NumPy, etc.)
  • Ability to communicate and interact with a wide range of users, from very technical to non-technical backgrounds.
  • Strong analytical skills with demonstrated attention to detail.

Apply