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Flexible Remote Machine Learning Engineer Jobs in Colorado

Signifyd

Senior Machine Learning Engineer I // II

Denver, CO · On-site +1

$107K - $147K/yr

... learning. #LI-Remote Benefits in our US offices: * Discretionary Time Off Policy (Unlimited ... Flexible Spending Account (FSA) * Short Term and Long Term Disability Insurance * Life Insurance

Maxar

Algorithm Engineer

Westminster, CO · On-site +1

$102K - $136K/yr

Flexible and willing to transition easily between tasks that may vary in scope and technical focus ... remote sensing applications. * Experience with machine learning frameworks and modern AI ...

Maxar

Senior Algorithm Engineer

Westminster, CO · On-site +1

$124K - $165K/yr

Research, prototype, and deploy innovative solutions leveraging machine learning and computer ... Bachelors degree in Computer Science, Computer Engineering, Applied Mathematics, Physics, Remote ...

Wsgr

Innovations and AI Solutions Engineer

Boulder, CO · On-site +1

This position is available as a hybrid or remote work schedule. Essential Duties, Responsibilities ... Design, build and implement machine learning models, including the development of AI Models and ...

Booz Allen Hamilton, Inc.

Data Scientist, Lead

Aurora, CO · On-site +1

$112K - $257K/yr

... machine learning, probability modeling, data mining, data engineering, or data warehousing, or ... Remote : If this position is listed as remote, there may still be occasions when you are required ...

New

Five and Fly

Analytics Engineering Intern

Denver, CO · On-site +1

$17.25 - $22.50/hr

Remote Description We are looking for an Analytics Engineering Intern who is eager to learn and ... Interest in AI, machine learning, or intelligent automation.

Magnite

Senior Engineer

Broomfield, CO · On-site +1

$135K - $175K/yr

Remote At Magnite, we cultivate an environment of continuous growth and collaboration. Our work ... Through a combination of near-real-time data pipelines, machine learning techniques, and real-time ...

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Flexible Remote Machine Learning Engineer information

How does a flexible remote work arrangement impact collaboration and project delivery for machine learning engineers?

In a flexible remote setting, Machine Learning Engineers often rely on digital collaboration tools to communicate with team members and manage projects. This setup allows for asynchronous work, enabling engineers to focus deeply on model development and data analysis without constant interruptions. However, it also means proactively scheduling check-ins and maintaining clear documentation are crucial to ensure alignment across distributed teams. While remote work offers autonomy and work-life balance, successful engineers build strong communication habits to keep projects on track and foster effective collaboration with data scientists, product managers, and software engineers.

What is a flexible remote machine learning engineer?

A Flexible Remote Machine Learning Engineer is a professional who designs, builds, and deploys machine learning models while working remotely, often with flexible hours. They use programming, data analysis, and statistical skills to create algorithms that solve real-world problems, collaborating with teams through digital communication tools. This role allows for a better work-life balance and can be performed from anywhere with a reliable internet connection. Flexible remote positions are especially popular in the tech industry, where project-based work and results matter more than strict office hours.

What is the difference between Flexible Remote Machine Learning Engineer vs Data Scientist?

AspectFlexible Remote Machine Learning EngineerData Scientist
Required CredentialsBachelor's or higher in CS, ML, or related fields; experience with ML frameworksBachelor's or higher in CS, Statistics, or related fields; proficiency in data analysis
Work EnvironmentRemote, collaborative teams, project-basedRemote or on-site, data analysis-focused
Industry UsageTech, finance, healthcare, e-commerceTech, marketing, finance, research
Common Search IntentRoles involving ML model development and deploymentRoles focused on data analysis and insights

The main difference is that a Flexible Remote Machine Learning Engineer primarily develops and deploys machine learning models, while a Data Scientist focuses on analyzing data to generate insights. Both roles often require similar educational backgrounds and can be remote, but their core responsibilities differ in application and focus.

What are the key skills and qualifications needed to thrive as a flexible remote machine learning engineer?

To thrive as a Flexible Remote Machine Learning Engineer, you need strong programming skills (especially in Python), a solid understanding of machine learning algorithms, and typically a degree in computer science or a related field. Familiarity with tools like TensorFlow, PyTorch, cloud platforms (AWS, GCP, or Azure), and experience with data pipelines are essential, and certifications in machine learning or cloud technologies can be advantageous. Excellent communication, self-motivation, and time management skills help you collaborate effectively and stay productive in a remote, flexible work environment. These skills ensure you can independently deliver high-quality ML solutions, maintain clear team communication, and adapt to evolving project requirements.

What are the most commonly searched types of Remote Machine Learning Engineer jobs in Colorado?

The most popular types of Remote Machine Learning Engineer jobs in Colorado are:

What are popular job titles related to Flexible Remote Machine Learning Engineer jobs in Colorado?

For Flexible Remote Machine Learning Engineer jobs in Colorado, the most frequently searched job titles are:

What job categories do people searching Flexible Remote Machine Learning Engineer jobs in Colorado look for?

The top searched job categories for Flexible Remote Machine Learning Engineer jobs in Colorado are:

What cities in Colorado are hiring for Flexible Remote Machine Learning Engineer jobs?

Cities in Colorado with the most Flexible Remote Machine Learning Engineer job openings:

Flexible Remote Machine Learning Engineer jobs near you

Senior Machine Learning Engineer I // II

Signifyd

Denver, CO • On-site, Remote

$107K - $147K/yr

Full-time

Medical, Dental, Vision, Life, Retirement

Re-posted yesterday

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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