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Adversarial Machine Learning Jobs in Colorado (NOW HIRING)

Signifyd

Senior Machine Learning Engineer I // II

Denver, CO · On-site +1

$107K - $147K/yr

We seek equally motivated individuals who are passionate about keeping our customers safe while pulling the field of adversarial machine learning forward. The Role As a Senior Machine Learning ...

Deloitte

AI Data Engineer - Manager

Denver, CO · On-site

... machine learning models and large language models. • Conduct research to provide technical ... adversarial samples. • Help AI product managers and business stakeholders understand the ...

CACI International, Inc.

AI/ML Engineer

Aurora, CO · On-site

MS or PhD in machine learning, computer science, mathematics, or relevant fields * Experience ... Generative Adversarial Networks and Variational Autoencoders * Reinforcement learning and ...

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Adversarial Machine Learning information

What are some common challenges faced by professionals working in Adversarial Machine Learning roles?

Adversarial Machine Learning professionals often face the challenge of staying ahead of rapidly evolving attack techniques that can compromise model integrity and security. Managing the balance between model performance and robustness is another key difficulty, as defenses against adversarial attacks can sometimes reduce accuracy or increase computational costs. Collaboration with data scientists, security teams, and software engineers is vital for developing resilient models and implementing effective defenses. Staying current with the latest research and tools is essential for success in this dynamic field.

What are the key skills and qualifications needed to thrive as an Adversarial Machine Learning specialist, and why are they important?

To excel in Adversarial Machine Learning, you need a strong background in machine learning, deep learning, statistics, and computer science, typically supported by an advanced degree in a related field. Familiarity with frameworks like TensorFlow or PyTorch, experience with adversarial attack and defense libraries, and knowledge of security protocols are crucial. Creative problem-solving, critical thinking, and strong communication skills help in designing robust models and explaining complex threats to stakeholders. These competencies are vital to anticipate vulnerabilities, safeguard AI systems, and ensure the reliability of machine learning models in real-world applications.

What is the difference between Adversarial Machine Learning vs Data Scientist?

AspectAdversarial Machine LearningData Scientist
CredentialsKnowledge of machine learning, cybersecurity, and threat detectionDegree in data science, statistics, or related fields
Work EnvironmentResearch labs, cybersecurity teams, AI developmentBusiness analytics, data analysis, model development
Industry UsageAI security, cybersecurity, machine learning researchBusiness, finance, healthcare, tech companies

Adversarial Machine Learning focuses on understanding and defending AI models against malicious inputs, often within cybersecurity contexts. Data Scientists analyze data to extract insights, build models, and support decision-making across various industries. While both roles require machine learning knowledge, Adversarial Machine Learning emphasizes security and robustness, whereas Data Scientists focus on data analysis and predictive modeling.

What is adversarial machine learning?

Adversarial machine learning is a field of study focused on understanding and defending against attacks that manipulate machine learning models by feeding them deceptive input, known as adversarial examples. These attacks can cause models to make incorrect predictions, raising concerns about the security and reliability of AI systems, especially in critical applications like image recognition and autonomous vehicles. Researchers in this area develop techniques to detect, prevent, and mitigate these vulnerabilities to make machine learning systems more robust.
What are popular job titles related to Adversarial Machine Learning jobs in Colorado? For Adversarial Machine Learning jobs in Colorado, the most frequently searched job titles are:
What job categories do people searching Adversarial Machine Learning jobs in Colorado look for? The top searched job categories for Adversarial Machine Learning jobs in Colorado are:
What cities in Colorado are hiring for Adversarial Machine Learning jobs? Cities in Colorado with the most Adversarial Machine Learning job openings:
Adversarial Machine Learning jobs near you
Senior Machine Learning Engineer I // II

Senior Machine Learning Engineer I // II

Signifyd

Denver, CO • On-site, Remote

$107K - $147K/yr

Full-time

Medical, Dental, Vision, Life, Retirement

Posted 6 days ago

Job description

At Signifyd, we help merchants confidently grow their businesses by building trusted relationships with their customers. Our advanced technology, combined with a team genuinely invested in our clients' success, creates frictionless shopping experiences, approving more good orders, protecting revenue, and keeping customers happy.
Trusted by thousands of leading merchants across more than 100 countries, we securely process billions of transactions each year. Our people are the heart of everything we do, driving our mission forward with commitment, empathy, and creativity. Join us on our mission to empower confident, fraud-free commerce by helping online retailers provide superior customer experiences and eliminate fraud. Learn about our company values here!
The Senior Machine Learning Engineer will join our ML team. This team is responsible for building, maintaining, and monitoring the production ML models and offline experimentation frameworks that are at the core of Signifyd's product. This includes the core fraud detection model that decides the majority of our traffic, alongside our model training and evaluation infrastructure. We work closely with Platform Engineering teams to contribute novel modeling methods, advanced feature engineering, and robust statistical practices.
Our Culture
We value tenacity, curiosity, and a hunger for learning. Our adversaries are highly motivated fraudsters looking to exploit any gap. We seek equally motivated individuals who are passionate about keeping our customers safe while pulling the field of adversarial machine learning forward.
The Role
As a Senior Machine Learning Engineer, you will be a driver of technical execution within the ML team. You won't just build models-you'll own the end-to-end lifecycle of high-impact ML projects, from offline experimentation to deployment to production. You will be responsible for improving model performance, refining our experimentation processes, and ensuring our fraud detection systems are robust, scalable, and scientifically sound.
Responsibilities:
  • Expand ML Capabilities - Identify, prototype, and integrate new ML technologies and infrastructure to enhance fraud detection effectiveness and scalability.
  • Enable High-Velocity Experimentation - Own the design and implementation of ML pipeline components that accelerate our innovation
  • Collaborate Across Functions - Partner with Product, Engineering, and Risk teams to translate business requirements into technical solutions and ensure ML initiatives align with customer needs.
  • Raise the Bar - Foster a culture of technical excellence by championing best practices in testing, documentation, model monitoring, and development.

Requirements:
  • Education: A degree in Computer Science, Statistics, or a comparable quantitative field.
  • Experience: 4-6+ years of post-undergrad work experience in a production-grade ML environment.
  • Technical Depth: Strong foundation in machine learning theory, statistical evaluation, and experience with supervised/unsupervised learning at scale.
  • Execution Focus: Proven track record of taking ML projects from research/prototype to high-scale production environments.
  • Communication: Ability to communicate technical findings clearly to both technical peers and non-technical stakeholders.
  • Tech Stack: Proficiency in Python, SQL, key ML libraries, and Spark
  • Mindset: A strong outcome-oriented mindset-you care about the "why" behind the models and the business impact they create.
  • Attention to detail is critical in fraud prevention. To demonstrate this, please start your response to the first application question with the word 'Stochastic'

Nice to have:
  • Previous experience in fraud, fintech, payments, or e-commerce.
  • Passion for writing well-tested production-grade code
  • A Master's Degree or PhD.
Why Join Us?
  • Make an Impact - Your work will directly shape the future of fraud prevention, protecting billions of payments.
  • Lead & Grow - Drive high-visibility initiatives and develop leadership skills in a fast-paced, high-growth environment.
  • Innovate at Scale - Work with cutting-edge ML technologies and experiment freely to push the boundaries of what's possible.
  • Collaborative Culture - Join a team that values curiosity, ownership, and continuous learning.

#LI-Remote
Benefits in our US offices:
  • Discretionary Time Off Policy (Unlimited!)
  • 401K Match
  • Stock Options
  • Annual Performance Bonus or Commissions
  • Paid Parental Leave (12 weeks)
  • On-Demand Therapy for all employees & their dependents
  • Dedicated learning budget through Learnerbly
  • Health Insurance
  • Dental Insurance
  • Vision Insurance
  • Flexible Spending Account (FSA)
  • Short Term and Long Term Disability Insurance
  • Life Insurance
  • Company Social Events
  • Signifyd Swag

Compensation:
In the United States, each work location is assigned a specific pay zone, which determines the salary range for a given position. The starting base salary for the selected candidate will be based on a variety of factors, including job-related skills, experience, qualifications, geographic location, and current market conditions.
Base Salary Ranges by Pay Zone:
  • Tier 1 (NYC/SF Bay Area/Seattle): $160,000 - $190,000 annually
  • Tier 2 (DC Metro/Austin/Chicago/Denver/Boston/Los Angeles/San Diego):$150,000 - $180,000 annually
  • Tier 3 (US - All Other): $140,000 - $170,000 annually
Equity: This role is eligible for a stock option grant of 4,000 stock options, based on the position level and internal compensation guidelines.
Bonus: This role is eligible for an annual performance bonus of up to 10% of base salary.
We want to provide an inclusive interview experience for all, including people with disabilities. We are happy to provide reasonable accommodations to candidates in need of individualized support during the hiring process.
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