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Machine Learning Quantum Computing Jobs in Colorado

Machine Learning Engineer LOCATIONAurora, CO 80014 CLEARANCETS/SCI Full Poly (Please note this ... Knowledge of edge computing and model optimization for deployment PLUG IN to CYMERTEK - And design ...

Machine Learning Engineer LOCATION Aurora, CO 80014 CLEARANCE TS/SCI Full Poly (Please note this ... Knowledge of edge computing and model optimization for deployment PLUG IN to CYMERTEK - And design ...

Sr Software Engineer

Boulder, CO · On-site

$106K - $145K/yr

... our Quantum Computing mission forward. At Infleqtion we embrace a startup mentality driven by ... Domain-specific experience in statistics, machine learning, or AMO physics * Experience with Numpy ...

Sr Software Engineer

Boulder, CO · On-site

$106K - $145K/yr

... our Quantum Computing mission forward. At Infleqtion we embrace a startup mentality driven by ... Domain-specific experience in statistics, machine learning, or AMO physics * Experience with Numpy ...

Apply Early

Sr Software Engineer

Boulder, CO · On-site

$106K - $145K/yr

... our Quantum Computing mission forward. At Infleqtion we embrace a startup mentality driven by ... Domain-specific experience in statistics, machine learning, or AMO physics * Experience with Numpy ...

$89K - $157K/yr

The Space AI Talent Center is seeking a highly skilled AI/ML Machine Learning Engineer to join a ... computing platform • Excellent written and verbal communication skills • Ability to work in a ...

$132K - $234K/yr

The Space AI Talent Center is seeking a highly skilled AI/ML Machine Learning Engineer to join a ... computing platform • Excellent written and verbal communication skills • Ability to work in a ...

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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 Colorado? For Machine Learning Quantum Computing jobs in Colorado, the most frequently searched job titles are:
What job categories do people searching Machine Learning Quantum Computing jobs in Colorado look for? The top searched job categories for Machine Learning Quantum Computing jobs in Colorado are:
What cities in Colorado are hiring for Machine Learning Quantum Computing jobs? Cities in Colorado with the most Machine Learning Quantum Computing job openings:
Infographic showing various Machine Learning Quantum Computing job openings in Colorado as of June 2026, with employment types broken down into 94% Full Time, 5% Part Time, and 1% Nights. Highlights an 66% Physical, 4% Hybrid, and 30% Remote job distribution.
Machine Learning Engineer

$145K - $266K/yr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 19 days ago


Keysight Technologies rating

8.1

Company rating: 8.1 out of 10

Based on 20 frontline employees who took The Breakroom Quiz

41st of 141 rated electronics manufacturers


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

1. 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.

2. 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.

3. 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).

4. 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.

5. 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.

#LI-MO1

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

California Pay rangeMIN $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
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.

#LI-MO1

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

California Pay rangeMIN $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
Education:UNAVAILABLEEmployment Type: UNAVAILABLE

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