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Machine Learning Defense Jobs in Arizona (NOW HIRING)

Rocket Lab Corporation

Machine Learning Engineer II

Tucson, AZ · On-site

$92K - $126K/yr

... defense initiatives. The team has built spacecraft, payloads, and components for missions to the ... MACHINE LEARNING ENGINEER II Rocket Lab's Optical Systems division solves mission-critical space ...

Honeywell International, Inc.

Lead AI Engineer

Phoenix, AZ · On-site

$96K - $126K/yr

... based machine learning models. This role focuses on applying artificial intelligence, physics ... HONA), we're launching as an independent, publicly traded aerospace and defense company built on a ...

MUFG

Global Red Team AI Engineer, AVP

Tempe, AZ · Hybrid

Coordinate with defensive, engineering, risk, and business stakeholders to ensure engagements are ... Exposure to AI security, LLM testing, AI governance, data security, machine learning workflows, or ...

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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 Arizona?

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

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

Machine Learning Defense jobs near you

Machine Learning Engineer II

Tucson, AZ • On-site

Rocket Lab Corporation
Aerospace Product and Parts Manufacturing • 201 - 500 employees
Learn more about Rocket Lab Corporationexternal

$92K - $126K/yr

Full-time

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

Rocket Lab rating

9.2

Company rating: 9.2 out of 10

Based on 14 frontline employees who took The Breakroom Quiz

Job description

SPACE SYSTEMS

At Rocket Lab, we're not just launching rockets - we're building the future of space. Our Space Systems team builds everything from complete spacecraft, precision payloads to the components and subsystems that allow them to thrive in space, like solar panels, flight software, star trackers, optical systems, separation systems, radios, and more.

Our Space Systems team has enabled more than 1,700 missions, ranging from interplanetary exploration, in-space manufacturing to national security and defense initiatives. The team has built spacecraft, payloads, and components for missions to the Moon and Mars, working with partners including NASA, the Space Development Agency, and the U.S. Space Force. Whether it's a single high-performance spacecraft, constellation, or the vertically integrated components that help them get to space - our world class Space Systems team is empowering some of the boldest and most ambitious space missions.

MACHINE LEARNING ENGINEER II

Rocket Lab's Optical Systems division solves mission-critical space domain and Intelligence, Surveillance, and Reconnaissance (ISR) challenges for Department of Defense (DoD) and Intelligence Community (IC) customers. Our vision is to revolutionize the space-based payload market with innovative and novel designs for space, terrestrial, and airborne environments. Building on more than 20 years of electro-optical and infrared systems innovation, Optical Systems delivers solutions to the warfighter for responsive, scalable sensing solutions across all orbital domains.

As a Machine Learning Engineer II based at our Optical Systems sites in Tucson, AZ, you will have the opportunity to support Tranche 3 of the U.S. Space Development Agency's (SDA) Proliferated Warfighter Space Architecture (PWSA) and beyond by building deep learning neural networks for advanced Electro-Optical (EO/IR) image processing.

WHAT YOU'LL DO

  • Contribute your experience to developing solutions for real-world problems.
  • Design, train, and deploy machine learning models for Optical Systems applications
  • Build and maintain ML pipelines for data ingestion, feature engineering, training, and inference.
  • Collaborate with other researchers/engineers on artificial intelligence, machine learning, and computer vision.
  • Preform rapid prototyping and enhanced development to be integrated into operational systems.
  • Perform troubleshooting, bug fixes, and maintenance of existing and new systems.
  • Stay current with ML research and evaluate new tools, frameworks, and techniques

 WHAT WE'RE LOOKING FOR IN A SENIOR MACHINE LEARNING ENGINEER I:

  • Bachelor's degree and 2+ years of experience, master's degree or a Ph.D. in Computer Science, Electrical and Computer Engineering, Mechanical Engineering, Physics, or related field
  • Strong background in machine learning including model selection, architecting, training, validation, testing, and deployment
  • Experience in building deep learning neural network for computer vision, image processing, or video analysis (e.g., object detection, image segmentation, and tracking)
  • Strong math background, particularly linear algebra
  • Proficiency in Python
  • Experience with deep learning libraries (Keras, TensorFlow, Pytorch, etc)
  • Software engineering fundamentals: version control, testing, CI/CD, containerization
  • S. citizenship is required, due to program requirements
  • Ability to obtain and maintain an U.S. Government Security Clearance

NICE TO HAVE: 

  • Proficiency in C/C++/Rust
  • Experience curating quality, real-world datasets for training deep learning models
  • TS/SCI security clearance

This position may require prolonged periods of sitting, standing, walking, computer work, and occasional exposure to moderate levels of noise, dust, and fumes in production areas.

What Rocket Lab employees say

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