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Machine Learning Defense Jobs in Kentucky (NOW HIRING)

$170 - $240/hr

As a Senior Machine Learning Engineer on the Trust Frontier AI team, you will actively contribute ... Partner with front line defense teams to validate solutions through experiments and holdouts, and ...

$129 - $215/hr

... Defense, and Federal Civilian sectors. Dive into innovation in Digital Transformation ... The Machine Learning Engineer will leverage their strong technical background and knowledge to ...

$166 - $220/hr

Anduril Industries is a defense technology company with a mission to transform U.S. and allied ... About the Role We are seeking a Machine Learning Perception Engineer to join our Perception team in ...

$180 - $240/hr

Machine Learning Engineer, Detection and Tracking * Full-time * Washington, DC Who we are Helsing ... Background in defense, intelligence, or other mission-critical environments Join Helsing and work ...

$180 - $300/hr

... defense AI startup building technology to detect and conduct a novel class of AI-powered cyber ... Signal processing * Machine learning and sequential modelling * Computational social science

New

$195 - $259/hr

Cybersecurity & Defensive AI: Leverage machine learning for cybersecurity by integrating AI-driven threat detection, fraud prevention algorithms, and defensive cyber operations into system ...

$110 - $175/hr

Scientific Applications & Research Associates, Inc. (SARA) is a world‑class Defense Research and Development enterprise with more than 35 years of proven innovation. We create new and emerging ...

$78 - $176/hr

We're looking for an engineer like you to create artificial intelligence (AI) and machine learning(ML)enabled solutions that help solve our toughest challenges facing the Defense and Intelligence ...

New

$170 - $230/hr

Computer Vision & Machine Learning Engineering Manager for Autonomous Anti-Drone Systems Company Overview: Allen Control Systems (ACS) is a cutting-edge defense startup founded by two former Navy ...

$150 - $195/hr

S. Federal Government, Department of Defense (DoD), Intelligence Community (IC), and National ... Machine Learning (QML), Quantum Fourier Transform (QFT), Grover's Search, and other quantum ...

$110 - $185/hr

Overview LMI is seeking a Machine Learning Operations Engineer (ML Ops Engineer) to support the ... With a focus on agility and collaboration, LMI serves the defense, space, healthcare, and energy ...

$150 - $230/hr

... Defense (A&D) manufacturing. A&D manufacturing represents one of the most complex, high‑stakes ... D. in Computer Science, Machine Learning, Data Science, Electrical Engineering, or a related ...

$108 - $195/hr

Familiarity with machine-learning-based reconstruction or inference methods, including ... Leidos Defense provides a diverse portfolio of systems, solutions, and services covering land, sea ...

New

$140 - $188/hr

... machine learning development, and data integration efforts within Army Vantage and other Department of Defense (DoD) platforms. This role is primarily remote; however, candidates must be able to ...

New

$180 - $247/hr

... machine learning to optimally engineer, additively manufacture, and flexibly assemble complex ... Department of Defense, allied governments, and defense prime contractors. This role requires ...

$150 - $220/hr

... Defense and Intelligence Business unit serving the Intelligence Community as our primary customer. Essential Functions: As a Senior Data Scientist, you will: * Develop and implement machine learning ...

$99 - $225/hr

As an experienced AI/ML engineer, you know that machine learning and generative AI are critical to ... Work with us to solve real-world challenges and define AI/ML strategy for national defense mission ...

New

$130 - $180/hr

... defense. The company leverages over a decade of advanced research in robotics and machine learning, as well as a field-test forward ethos, to deliver combined capabilities for unit commanders. Our ...

$135 - $190/hr

S Department of Defense, Intelligence Community, and commercial customers. We are seeking a ... machine learning (AI/ML) for signal processing, and government and industry open software ...

$216 - $270/hr

... generative AI, defense, and autonomous vehicles. We partner with leading enterprises and ... About the Role As a Machine Learning Engineer on Agent Oversight, you will drive the end-to-end ...

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Showing results 1-20

Machine Learning Defense information

What is machine learning defense?

Machine learning defense refers to techniques and strategies designed to protect machine learning models from various security threats, such as adversarial attacks, data poisoning, and model theft. These defenses can include methods like adversarial training, input sanitization, and robust model architectures. The goal is to ensure that machine learning systems remain accurate, reliable, and safe even when faced with malicious attempts to manipulate or exploit them. As machine learning becomes more widely adopted, the importance of effective defenses continues to grow.

What are some common challenges faced by professionals in machine learning defense roles, and how can they be addressed?

Professionals in Machine Learning Defense often encounter challenges such as staying ahead of adversarial attacks, managing model robustness, and keeping up with rapidly evolving threat landscapes. Addressing these challenges typically requires continuous learning, collaboration with cybersecurity and data science teams, and implementing rigorous testing and monitoring frameworks for deployed models. Proactively participating in industry forums and staying updated on the latest research also help in identifying emerging threats and mitigation strategies.

What are the key skills and qualifications needed to thrive as a machine learning defense professional, and why are they important?

To thrive as a Machine Learning Defense professional, you need a strong background in computer science, cybersecurity, and machine learning, often supported by degrees in these fields or related certifications. Familiarity with frameworks like TensorFlow or PyTorch, experience with adversarial machine learning techniques, and knowledge of security protocols are typically required. Critical thinking, problem-solving, and strong communication skills are essential for anticipating threats and collaborating with interdisciplinary teams. These skills ensure that AI systems remain robust and secure against evolving cyber threats, protecting sensitive data and organizational integrity.

What are popular job titles related to Machine Learning Defense jobs in Kentucky?

For Machine Learning Defense jobs in Kentucky, the most frequently searched job titles are:

What cities in Kentucky are hiring for Machine Learning Defense jobs?

Cities in Kentucky with the most Machine Learning Defense job openings:

Senior Machine Learning Engineer, Trust

airbnb, Inc.

On-site

$170 - $240/hr

Other

Posted 7 days ago


Airbnb rating

6.1

Company rating: 6.1 out of 10

Based on 10 frontline employees who took The Breakroom Quiz

15th of 21 rated holiday rentals


Job description

The Community You Will Join:

Everyone at Airbnb thinks about trust, but our team obsesses over it daily. At the core of trust is safety, and thus we spend a significant amount of our time and energy keeping the community safe. The Trust team is responsible for developing the technology that helps protect our community and platform from fraud while also ensuring our hosts, guests, homes, and experiences meet our high standards. We constantly work to fight against online fraud (such as monetary loss, compromised accounts, spam and scam in messages, fake inventory, etc.) as well as offline fraud (theft, property damage, personal safety, etc.). We also work on onboarding and screening of users, and think about complex topics like identity and reputation to ensure that every interaction with Airbnb helps build trust in us and our community.

The Trust Frontier AI team is where new AI technology for Trust gets invented and proven. We build specialized models for mission-critical trust and safety problems, develop the AI agents and agentic capabilities that automate trust decisions, and create the benchmarks and evaluation harnesses that keep decision quality high as those agents take on more autonomy. We work on problems before the answer is known — prototyping, experimenting, and iterating with our partner teams until a solution proves itself against real business and top line metrics.

You'll work side-by-side with talented product managers, data scientists, software engineers, fraud intelligence, and operations teams. Together, you'll design and build ML solutions that have direct, meaningful impact on user trust, business success, and the global Airbnb community.

The Difference You Will Make:

As a Senior Machine Learning Engineer on the Trust Frontier AI team, you will actively contribute code and ideas that shape the next generation of AI systems protecting millions of Airbnb users. You'll own and deliver ML projects end-to-end, from framing an ambiguous problem and prototyping a solution, to training and productionizing models, to proving impact on top line metrics with front line teams.

You'll work on abuse behavior detection that spans multiple defenses, on AI agents that make trust decisions autonomously, and on the evaluation and benchmarking work that makes those decisions trustworthy. Much of this work is early: you will help decide what to build, not only how to build it, and you'll see it through to measurable impact on the platform.

A Typical Day:
  • Frame and prototype ML and agentic solutions for problems that do not yet have an established approach, in partnership with product managers, data scientists, and front line defense teams.
  • Design, build, and productionize end-to-end Machine Learning pipelines — including feature engineering, model training, evaluation, and deployment — for both batch and real-time use cases.
  • Build and improve abuse behavior detection that generalizes across defenses.
  • Design, launch, and iterate on AI agents that automate trust decisions, including orchestration, tool interfaces, and the guardrails that hold quality steady as autonomy increases.
  • Build benchmarks, evaluation harnesses, and instrumentation that let us measure agentic and model decision quality objectively, and use them to drive real improvements.
  • Develop specialized models for trust and safety use cases, and use LLMs and AI agents to accelerate how we build models.
  • Write, review, and ship clean, testable code — whether training a new model, improving an existing pipeline, or optimizing a feature for scalability and reliability.
  • Work with large-scale structured and unstructured data to continuously improve ML models for Airbnb product, business, and operational use cases.
  • Partner with front line defense teams to validate solutions through experiments and holdouts, and quantify their impact on business and operational metrics.
  • Participate in code reviews, design discussions, and cross-team collaborations to contribute to a high-quality ML engineering culture.
Your Expertise:
  • 5-10 years of industry experience in applied Machine Learning, with a track record of building and productionizing models at scale.
  • 1-2+ years of hands-on experience with LLMs and GenAI technologies, including building with agentic frameworks, orchestration, and evaluation.
  • Strong programming skills in Python (required) and familiarity with Scala, Java, or equivalent.
  • Solid understanding of Machine Learning best practices — e.g., training/serving skew minimization, A/B testing, feature engineering, model selection — and algorithms such as gradient boosted trees, neural networks, transformers, and deep learning.
  • Experience with ML frameworks and tooling such as TensorFlow, PyTorch, or equivalent.
  • Experience with data engineering and building end-to-end ML pipelines, including both batch and real-time systems.
  • Experience designing evaluation methodology for ML or LLM systems — benchmarks, ground truth, offline/online metrics, calibration.
  • Comfort with ambiguity and a bias toward action: you can take a loosely defined problem, scope it, prototype quickly, and drive it to a measurable outcome.
  • Exposure to architectural patterns of large, high-scale software applications (e.g., well-designed APIs, high-volume data pipelines, efficient algorithms).
  • Experience with test-driven development, incremental delivery, and deployment practices.
  • Experience with multimodal models (vision, document, or speech) is a plus.
  • Exposure to the Trust and Risk domain (e.g., fraud detection, anomaly detection, identity, account integrity) is a plus.
  • A Bachelor's, Master's, or PhD in CS/ML or a related field.
Your Location:

This position is US - Remote Eligible. The role may include occasional work at an Airbnb office or attendance at offsites, as agreed to with your manager. While the position is Remote Eligible, you must live in a state where Airbnb, Inc. has a registered entity. Click here for the up-to-date list of excluded states. This list is continuously evolving, so please check back with us if the state you live in is on the exclusion list. If your position is employed by another Airbnb entity, your recruiter will inform you what states you are eligible to work from.

Our Commitment To Inclusion & Belonging:

Airbnb is committed to working with the broadest talent pool possible. We believe diverse ideas foster innovation and engagement, and allow us to attract creatively-led people, and to develop the best products, services and solutions. All qualified individuals are encouraged to apply.

We strive to also provide a disability inclusive application and interview process. If you are a candidate with a disability and require reasonable accommodation in order to submit an application, please contact us at: reasonableaccommodations@airbnb.com . Please include your full name, the role you’re applying for and the accommodation necessary to assist you with the recruiting process.

We ask that you only reach out to us if you are a candidate whose disability prevents you from being able to complete our online application.

How We'll Take Care of You:

Our job titles may span more than one career level. The actual base pay is dependent upon many factors, such as: training, transferable skills, work experience, business needs and market demands. The base pay range is subject to change and may be modified in the future. This role may also be eligible for bonus, equity, benefits, and Employee Travel Credits.

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What Airbnb employees say

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