1

Internship Ibm Quantum Machine Learning Jobs in Colorado

... quantum, aerospace, defense, and semiconductor markets for customers in over 100 countries. Learn ... We are seeking a Machine Learning Engineer to lead the design, development, and deployment of ...

Quantum Research Engineer

Littleton, CO · On-site

$89K - $157K/yr

... machine learning tasks relevant to defense missions. • Performs system level modeling, runs test ... internships, or conference presentations. • Desire for candidate to reside in Colorado; depending ...

next page

Showing results 1-20

Internship Ibm Quantum Machine Learning information

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.

What are popular job titles related to Internship Ibm Quantum Machine Learning jobs in Colorado?

For Internship Ibm Quantum Machine Learning jobs in Colorado, the most frequently searched job titles are:

What job categories do people searching Internship Ibm Quantum Machine Learning jobs in Colorado look for?

The top searched job categories for Internship Ibm Quantum Machine Learning jobs in Colorado are:

Machine Learning Engineer

Socket.dev

Colorado Springs, CO • On-site

$135.15 - $225/hr

Other

Medical, Dental, Vision, Life, Retirement, PTO

This job post has expired today. Applications are no longer accepted.


Job description

Overview

Keysight is on the forefront of technology innovation, delivering breakthroughs and trusted insights in electronic design, simulation, prototyping, test, manufacturing, and optimization. Our ~15,000 employees create world-class solutions in communications, 5G, automotive, energy, quantum, aerospace, defense, and semiconductor markets for customers in over 100 countries. Learn more about what we do.


Our award-winning culture embraces a bold vision of where technology can take us and a passion for tackling challenging problems with industry-first solutions. We believe that when people feel a sense of belonging, they can be more creative, innovative, and thrive at all points in their careers.


We are seeking a Machine Learning Engineer to lead the design, development, and deployment of scalable machine learning models that power business decisions across the enterprise. This role combines technical depth in ML/AI with a strong understanding of business domains such as Sales, Service, Finance, Order Fulfillment, and Supply Chain. You will collaborate closely with Data Scientists, Data Engineers, and business partners to build production-ready solutions that drive measurable impact.


Responsibilities

  • Machine Learning Development & Deployment

  • Design and implement supervised and unsupervised models for predictive analytics, including churn prediction, demand forecasting, renewal risk scoring, and cross-sell/upsell opportunity identification.

  • Translate business problems into ML frameworks and production solutions that improve efficiency, revenue, or customer experience.

  • Build, optimize, and maintain ML pipelines using tools such as MLflow, Airflow, or Kubeflow.

  • Cross-Functional ML Use Cases

  • Partner with teams across Sales (e.g., lead scoring, next-best action), Customer Service (e.g., case deflection, sentiment analysis), Finance (e.g., revenue forecasting, fraud detection), Supply Chain (e.g., inventory optimization, ETA prediction), and Order Fulfillment (e.g., delivery risk modeling) to define impactful ML use cases.

  • Develop domain-specific models and continuously improve them using feedback loops and real-world performance data.

  • Model Governance and MLOps

  • Ensure robust model monitoring, versioning, and retraining strategies to keep models reliable in dynamic environments.

  • Work closely with DevOps and Data Engineering teams to automate deployment, CI/CD workflows, and cloud-native ML infrastructure (AWS/GCP/Azure).

  • Data Engineering and Feature Architecture

  • Collaborate with data engineers to define feature stores, data quality checks, and model-ready datasets on platforms like Snowflake or Databricks.

  • Perform feature selection, transformation, and engineering aligned with each domain’s business logic.

  • Communication & Stakeholder Collaboration

  • Present technical insights and model results to business and executive stakeholders in a clear, actionable format.

  • Work with Product Owners and Program Managers to scope, prioritize, and plan delivery of ML projects.


Qualifications

Required:



  • 4-6 years of experience in machine learning, data science, or AI engineering, with a strong software engineering foundation.

  • Proficiency in Python, and libraries such as scikit-learn, XGBoost, PyTorch, TensorFlow, or similar.

  • Experience deploying models into production using ML pipelines and orchestration frameworks.

  • Strong understanding of data structures, SQL, and cloud platforms (e.g., AWS SageMaker, Azure ML, or GCP Vertex AI).


Preferred

  • Experience supporting business functions such as Finance, Sales, or Operations with ML use cases.

  • Familiarity with MLOps tools (MLflow, SageMaker Pipelines, Feature Store).

  • Exposure to enterprise data platforms (e.g., Snowflake, Oracle Fusion, Salesforce).

  • Background in statistics, forecasting, optimization, or recommendation systems.


Careers Privacy Statement***Keysight is an Equal Opportunity Employer.***


California Pay range

  • MIN $145,970.00 - MAX $266,930.00

  • Colorado pay range: MIN $135,150.00- MAX $225,250.00

  • District of Columbia pay range: MIN $135,150.00- MAX $225,250.00

  • Hawaii pay range: MIN $135,150.00- MAX $225,250.00

  • Illinois pay range: MIN $135,150.00- MAX $225,250.00

  • Maryland pay range: MIN $135,150.00- MAX $225,250.00

  • Massachusetts pay range: MIN $145,970.00 - MAX $243,280.00

  • Minnesota pay range: MIN $135,150.00- MAX $225,250.00

  • New Jersey City pay range: MIN $145,970.00 - MAX $243,280.00

  • New York pay range: MIN $160,160.00 - MAX $266,930.00

  • Vermont pay range: MIN $135,150.00- MAX $225,250.00

  • Washington state pay range: MIN $145,970.00 - MAX $243,280.00


Note:


For other locations, pay ranges will vary by region


US Employees May Be Eligible For The Following Benefits

  • Medical, dental and vision

  • Health Savings Account

  • Health Care and Dependent Care Flexible Spending Accounts

  • Life, Accident, Disability insurance

  • Business Travel Accident and Business Travel Health

  • 401(k) Plan

  • Flexible Time Off, Paid Holidays

  • Paid Family Leave

  • Discounts, Perks

  • Tuition Reimbursement

  • Adoption Assistance

  • ESPP (Employee Stock Purchase Plan)

  • Restricted Stock Units

#J-18808-Ljbffr