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Smt Engineer
Actalent
Harrodsburg, KY
- $110,000 to $140,000 USD / year
This SMT Engineer role focuses on developing and optimizing surface mount technology (SMT) processes to support high-quality electronic manufacturing. You will investigate and implement new…
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Senior Security GRC Engineer, AI & Automation
American Express Global Business Travel
Frankfort, KY
AmexGBT’s Security GRC team is looking for a talented Senior Security GRC Engineer to design, build, and scale automation and AI-driven solutions that modernize our governance, risk, and…
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Head of Forward Deployed Engineering
Bausch + Lomb
Frankfort, KY
Bausch + Lomb is seeking a Head of Forward Deployed Engineer (FDE) to turn AI from pilots into production capability across B+L. This is a hands-on builder role embedded in manufacturing,…
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Software Engineer
Humana
Frankfort, KY
We are seeking a Software Engineer with experience developing, testing, and supporting production applications. The preferred candidate will have exposure to Epic or a similar healthcare…
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Java Full Stack Engineer with Spring boot/AWS Experience
Cognizant
Frankfort, KY
As a Java Full Stack Engineer with Spring boot/AWS exp, you will make an impact by designing and delivering scalable, cloud-native healthcare payer applications that improve payment…
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Director - Customer Response Engineering
Trellix
Frankfort, KY
The Director leads CRE globally and owns engineering response for strategic customers across our endpoint, data security, email, and network products. The role also owns prevention: finding…
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Network Operations Engineer
Meta
Frankfort, KY
Meta is seeking a Network Operations Engineer to join our Edge and Network Services (ENS) Foundation NetOps team. In this role, you will utilize your knowledge in hyperscale data center…
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AI Engineer
Humana
Louisville, KY
We are seeking an AI Engineer who will contribute to Generative AI initiatives at Humana, leveraging state-of-the-art LLMs to build applications. Our goal is to create safe AI solutions…
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Intelligent Automation Engineer
BrightSpring Health Services
LOUISVILLE, KY · Louisville, KY
…deployments, and collaborate with business, technology, security, data, and operations teams to deliver measurable…
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Lead AI and Data Science Engineer II
Deloitte
Louisville, KY
Do you have a strong background in machine learning and deep learning? Are you interested in utilizing your data science skills and leading a small team in a fast-paced environment to…
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MTS Software Development Engineer
Advanced Micro Devices, Inc
Santa Clara, CA
…significant and unique issues where analysis of situations or data requires an evaluation of intangibles. Drive projects or processes of significant technical importance. Exercise…
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PMTS Software Development Engineer
Advanced Micro Devices, Inc
San Jose, CA
Job Role and Responsibility: AMD, Inc., is hiring PMTS Software Development Engineer to Develop and maintain CI/CD pipelines with tools like Buildkite, GitHub Actions, and Jenkins to ensure…
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MTS Systems Engineer
Advanced Micro Devices, Inc
Austin, TX
Alternate combination of education and experience: Bachelor’s degree or foreign equivalent in Computer Science, Electronics Engineering, Information Technology Management, or related field…
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Sr. Software Development Engineer
Advanced Micro Devices, Inc
Austin, TX
Job Role and Responsibility: AMD, Inc., is hiring Sr. Software Development Engineer to Research, design, develop, and/or apply principles and techniques of computer science, engineering,…
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PMTS Software Development Engineer
Advanced Micro Devices, Inc
San Jose, CA
Job Role and Responsibility: AMD, Inc. is hiring PMTS Software Development Engineer to Work with architecture specialists to validate AI solutions for distributed training and inference…
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Sr. Manager Product Development Engineer
Advanced Micro Devices, Inc
Austin, TX
Job Role and Responsibility: AMD, Inc. is hiring Sr. Manager Product Development Engineer to Develop and/or test electrical/electronic components and/or systems for semiconductor products.…
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SMTS Software Development Engineer
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Austin, TX
Job Role and Responsibility: AMD, Inc., is hiring SMTS Software Development Engineer to Work with AMD’s architecture specialists to improve future products. Apply a data minded approach to…
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Sr. Software Development Engineer
Advanced Micro Devices, Inc
Austin, TX
Job Role and Responsibility: AMD, Inc., is hiring Sr. Software Development Engineer to Research, design, develop, and/or test operating systems-level software, compilers, and/or network…
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Sr. IT Engineer
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Job Role and Responsibility: Xilinx, Inc., a subsidiary of AMD, Inc., is hiring Sr. IT Engineer to Design, develop, and implement scalable data pipeline architectures using Kafka, Spark,…
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Sr. Software Development Engineer
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Austin, TX
Job Role and Responsibility: AMD, Inc. is hiring Sr. Software Development Engineer to research, design, develop, and test high-performance collective communication libraries, GPU…
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Software Development Engineer
Advanced Micro Devices, Inc
Austin, TX
Job Role and Responsibility: AMD, Inc., is hiring Software Development Engineer to Research, design, develop, and/or test operating systems-level software, compilers, and/or network…
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Software Development Engineer
Advanced Micro Devices, Inc
Austin, TX
Job Role and Responsibility: AMD, Inc., is hiring Software Development Engineer to Research, design, develop, and/or test operating systems-level software, compilers, and/or network…
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Software Development Engineer
Advanced Micro Devices, Inc
Austin, TX
Job Role and Responsibility: AMD, Inc., is hiring Software Development Engineer to Research, design, develop, and/or test operating systems-level software, compilers, and/or network…
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SMTS Software System Design Engineer
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Systems Design Engineer
Advanced Micro Devices, Inc
Austin, TX
Job Role and Responsibility: AMD, Inc., is hiring Systems Design Engineer to Research, design, develop, and/or test electronic components and systems for semiconductor and related device…

Keysight Technologies, Inc.

Machine Learning - PhD Intern (Modeling and Data Analysis)

Calabasas, CA, United States
Santa Rosa, CA, United States

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Job details

Apply by: Nov 6, 2027
Posting language: English
Posted: Nov 6, 2026

Original 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 ~16,800 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. About the Program Keysight's AI team builds adaptive engineering intelligence systems where measurement, simulation, and machine learning converge - models that learn from complex physical data and adapt to new design and testing conditions. This internship focuses on machine learning surrogate models for engineering simulation and measurement. High-fidelity simulations and physical measurements can dominate the design and test loop for RF, high-speed, and other engineering problems, and their cost limits how much of a design space an engineer can explore. You will develop models that predict engineering responses at a fraction of the cost, investigate how such models can be adapted efficiently as the design problem changes, and integrate the result into an engineering ML runtime environment. Role Overview You will design, train, and evaluate neural surrogate models that predict engineering responses from simulation or measurement data far faster than repeated high-fidelity simulation or physical characterization. This spans the full arc of the problem: generating or assembling the data, choosing and evaluating model architectures and output representations, establishing where accuracy holds and where it degrades, and quantifying the result against a realistic simulation or measurement budget. In the second phase you will study how a trained model can be specialized efficiently when the design problem shifts, using LoRA and related parameter-efficient adaptation methods. You will work alongside AI researchers, simulation and measurement experts, RF designers, and runtime engineers. Learning Outcomes

Apply modern machine learning to realistic engineering simulation and measurement data.
Learn how surrogate model accuracy depends on data quality, sampling strategy, representation choices, and simulation budget.
Develop practical experience with parameter-efficient adaptation methods such as LoRA under data-scarce engineering conditions.
Build fluency with uncertainty estimation, physical consistency checks, and engineering-relevant error analysis.
Take a research model from Python experimentation toward robust C++ and LibTorch integration.
Collaborate across machine learning, RF design, simulation, measurement, and runtime engineering disciplines.

Responsibilities

Generate parametric engineering datasets using simulation and/or measurement sources, with attention to sampling strategy and to numerical noise in the underlying data.
Design, train, and evaluate neural surrogate models for engineering response prediction.
Investigate how the choice of output representation affects accuracy, particularly across operating regions or frequency ranges where the response varies sharply.
Establish rigorous baselines and quantify accuracy as a function of simulation or measurement budget.
Evaluate LoRA and related parameter-efficient methods for specializing trained models to new problem settings, against full and partial fine-tuning.
Develop calibrated uncertainty estimates so that predictions can be trusted or deferred appropriately.
Verify physical consistency and engineering constraints - including passivity, causality, and reciprocity where applicable - and report engineering-relevant metrics including worst-case behavior.
Analyze the simulation corpus and model behavior: parameter sensitivity, response dimensionality, data quality and solver noise, and where prediction error concentrates across frequency and design space.
Prototype model training and inference integration in C++ and LibTorch within an engineering ML runtime environment.

Qualifications

Required Qualifications

Currently pursuing or recently completed a PhD in Machine Learning, Computer Science, Applied Mathematics, Electrical or Electronic Engineering, or a related technical field.
Hands-on experience across multiple neural architectures - transformers, neural operators, graph networks, CNNs - and sound judgment about which suits a given problem.
Strong Python and PyTorch, with experience training and debugging neural networks well beyond tutorial scale.
Strong C++ and hands-on LibTorch experience to implement and integrate models into a production runtime.
Solid grasp of transfer learning, fine-tuning, and parameter-efficient methods such as LoRA.
Strong applied statistics and exploratory data analysis, including sensitivity analysis and dimensionality reduction, and the judgment to diagnose a model from its errors rather than its aggregate score.
Experimental discipline: rigorous baselines, careful ablations, experiment tracking, reproducible results.
Willingness to learn the underlying physics rather than treat it as arbitrary numerical data. Mentorship will be provided.

Preferred Qualifications

Background in RF, microwave, high-speed digital, or test and measurement engineering; familiarity with S-parameters, filters, or interconnect.
Experience with EM simulation tools and their scripting interfaces, such as Keysight ADS, RFPro, Momentum, or comparable tools, or engineering measurement and test automation environments.
Experience with surrogate modeling, operator learning, physics-informed machine learning, or scientific machine learning generally.
Experience with uncertainty quantification, conformal prediction, or Gaussian process regression.
CUDA, cuDNN, or TensorRT experience, or prior experience shipping a research model in C++.

Prerequisites

Version control, modular code structure, and reproducible experiment pipelines.
CMake and Git workflows for sizeable C++ projects, and comfort profiling and debugging C++ code.
Ability to design an evaluation that answers a question rather than one that produces a favorable number.
Clear technical communication to both machine learning researchers and engineering stakeholders.

What This Internship Offers

Apply modern machine learning to physical engineering data in an industrial setting.
Learn parameter-efficient adaptation and transfer learning under severe data scarcity.
Develop working fluency in RF and high-speed concepts, measurement data, and simulation workflows.
Take a research model the full distance, from Python prototype to robust C++.
The opportunity to shape how machine learning accelerates engineering design and test at a company that builds both the simulators and the instruments that validate them.
Mentorship across machine learning, simulation, measurement, and RF design, with access to engineering tools and realistic engineering datasets.
A portfolio-defining project spanning scientific machine learning, efficient model adaptation, and real-world engineering applications.

CA Pay Range:

(PhD) $51-$56

Based on experience, education and skills, most offers will be between the minimum and the midpoint of the Salary Range listed above.

Note: For other locations, pay ranges will vary by region.

Candidates who wish to be considered must be enrolled in an accredited college/university as of September 2027.

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

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More about this job

Skills

Machine learning
Data analysis
Estimating
Research
Python
C++
ML
Computer science
PyTorch
Debugging
Statistics
Test automation
CMake
Git
Communication skills

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