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Machine Learning Quantum Computing Jobs in Colorado

You will develop and deploy new products at scale and leverage Workday's vast computing resources ... Deep understanding of statistical analysis, unsupervised and supervised machine learning algorithms ...

In this role, you willdevelop and deploy advanced analytics, machine learning, generative AI, and ... computing platforms to identify trends, opportunities, and actionable insights. * Design and ...

In this role, you will develop and deploy advanced analytics, machine learning, generative AI, and ... computing platforms to identify trends, opportunities, and actionable insights. Design and ...

Experience with Machine Learning libraries and frameworks such as Hugging Face and LangChain * Experience with Linux * Familiarity with using AWS cloud computing resources such as EC2, S3, Lambda ...

Experience with Machine Learning libraries and frameworks such as Hugging Face and LangChain * Experience with Linux * Familiarity with using AWS cloud computing resources such as EC2, S3, Lambda ...

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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 Performance Engineer

Machine Learning Performance Engineer

Keysight Technologies, Inc.

Loveland, CO • On-site

$160K - $266K/yr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 13 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 at 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.

The AI Models and Data Science team at Keysight AI Labs is hiring a ML Performance Engineer to make our training and inference stacks as fast as the math allows. You'll own end-to-end performance: profiling training workloads on multi-GPU clusters, writing custom CUDA kernels and LibTorch C++ extensions for hot paths, and optimizing inference for embedding in production software where every millisecond matters.

This role sits at the intersection of ML, systems engineering, and HPC. You'll work directly with MLEs and data scientists driving the modeling work, and with the engineering teams shipping these models into Keysight products.


Responsibilities
  • Profile and optimize training workloads — multi-GPU scaling efficiency, throughput, memory footprint, mixed precision, gradient checkpointing tradeoffs
  • Profile and optimize inference for low-latency, high-throughput deployment — quantization, graph optimization, kernel fusion, runtime selection
  • Write custom CUDA kernels and LibTorch (PyTorch C++) extensions to accelerate hot paths in both training and inference
  • Build and maintain serving infrastructure using ONNX Runtime, TensorRT, and similar — including C++ integration paths for embedding models inside production software
  • Partner with MLEs and data scientists on perf-aware architecture choices; partner with product engineering on deployment, versioning, and monitoring
  • Establish performance SLAs and regression tests so models stay fast as they evolve

Qualifications
  • 4+ years in ML engineering, performance engineering, or HPC, with substantial production ML experience
  • Strong Python and C++ — including LibTorch / PyTorch C++ extensions in production
  • Hands-on experience optimizing both training and inference workloads (not just one)
  • CUDA experience required — comfortable profiling GPU code with Nsight and reasoning about occupancy, memory hierarchy, and kernel-level tradeoffs
  • Production deployment experience with ONNX Runtime, TensorRT, or equivalent inference runtimes
  • Solid software engineering fundamentals: testing, versioning, code review, monitoring
  • Experience with Docker and container-based deployment

Careers Privacy Statement
Keysight Technologies Inc. is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability or any other protected categories under all applicable laws.

The level of role and salary will be based on applicable experience, education and skills; Most offers will be between the minimum and the midpoint of the Salary Range listed below.

California Pay Range: MIN $160,160- MAX $266,930

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)

Qualifications:
  • 4+ years in ML engineering, performance engineering, or HPC, with substantial production ML experience
  • Strong Python and C++ — including LibTorch / PyTorch C++ extensions in production
  • Hands-on experience optimizing both training and inference workloads (not just one)
  • CUDA experience required — comfortable profiling GPU code with Nsight and reasoning about occupancy, memory hierarchy, and kernel-level tradeoffs
  • Production deployment experience with ONNX Runtime, TensorRT, or equivalent inference runtimes
  • Solid software engineering fundamentals: testing, versioning, code review, monitoring
  • Experience with Docker and container-based deployment

Careers Privacy Statement
Keysight Technologies Inc. is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability or any other protected categories under all applicable laws.

The level of role and salary will be based on applicable experience, education and skills; Most offers will be between the minimum and the midpoint of the Salary Range listed below.

California Pay Range: MIN $160,160- MAX $266,930

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)

Education:UNAVAILABLEEmployment Type: UNAVAILABLE

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