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Remote Embedded Machine Learning Jobs in Colorado

Signifyd

Senior Machine Learning Engineer I // II

Denver, CO · On-site +1

$107K - $147K/yr

The Senior Machine Learning Engineer will join our ML team. This team is responsible for building ... learning. #LI-Remote Benefits in our US offices: * Discretionary Time Off Policy (Unlimited ...

SparkFun Electronics

Embedded Software Engineer

Niwot, CO · On-site +1

$85K/yr

... machine learning, building a robot for school or prototyping your first (or tenth) product. No ... All embedded software is open source and community driven. SparkFun developed technology is given ...

Cleerly

Sr. Machine Learning Software Engineer

Denver, CO · On-site +1

$126K - $166K/yr

While we are mostly a remote company, travel is required for some team meetings and cross function ... About the Opportunity We are seeking a senior machine learning software engineer to design, build ...

Maxar

Senior Algorithm Engineer

Westminster, CO · On-site +1

$124K - $165K/yr

Experience with geospatial, photogrammetric, or remote sensing applications. * Masters or Ph.D. in a related technical discipline. * Experience with machine learning frameworks and modern AI ...

SciTec

Senior Numerical Algorithm Software Engineer

Boulder, CO · On-site +1

$127K - $167K/yr

Advance modeling, simulation, and machine learning toolchains, including development of reusable ... Knowledge of DoD or Intelligence Community mission systems, especially related to remote sensing or ...

CUJO AI

Director Platform Product Owner

Denver, CO · On-site +1

We use machine learning and real-world data to develop cybersecurity, device intelligence , network ... This position is fully remote. We are hiring across the US, UK, and Canada. In This Role, You Will:

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 ...

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All JobsEmbedded Machine Learning JobsRemote Embedded Machine Learning JobsRemote Embedded Machine Learning Jobs in Colorado

Remote Embedded Machine Learning information

What are the key skills and qualifications needed to thrive as a Remote Embedded Machine Learning Engineer, and why are they important?

To thrive as a Remote Embedded Machine Learning Engineer, you need a solid background in embedded systems, machine learning algorithms, and programming languages like C/C++ and Python, often supported by a degree in computer science, electrical engineering, or related fields. Familiarity with microcontrollers, edge AI frameworks (such as TensorFlow Lite or Edge Impulse), and version control systems is typically required. Strong problem-solving skills, effective communication, and self-motivation are essential soft skills for collaborating remotely and troubleshooting complex issues. These skills ensure successful deployment of intelligent solutions on resource-constrained devices and effective teamwork in distributed environments.

What is a Remote Embedded Machine Learning Engineer?

A Remote Embedded Machine Learning Engineer is a professional who develops and deploys machine learning models on embedded systems like microcontrollers, IoT devices, and edge hardware, all while working remotely. Their work involves optimizing algorithms to run efficiently on devices with limited computing power, memory, and battery life. These engineers typically use frameworks such as TensorFlow Lite or TinyML to design intelligent features that operate directly on hardware, enabling real-time decision-making without relying heavily on cloud connectivity. They collaborate with cross-functional teams and often troubleshoot both software and hardware issues from a remote location.

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

AspectRemote Embedded Machine LearningRemote Data Scientist
Required CredentialsBachelor's or Master's in Computer Science, Electrical Engineering, or related fields; experience with embedded systems and ML frameworksBachelor's or Master's in Data Science, Statistics, or related fields; proficiency in data analysis and ML algorithms
Work EnvironmentEmbedded hardware devices, IoT systems, real-time processing environmentsCloud platforms, data analysis labs, remote offices
Employer & Industry UsageTech companies, IoT device manufacturers, automotive, roboticsFinance, healthcare, marketing, tech firms

Remote Embedded Machine Learning specialists focus on integrating ML models into embedded hardware for real-time applications, often working with IoT and robotics. In contrast, Remote Data Scientists analyze large datasets to extract insights, primarily working in cloud or office environments. Both roles require strong analytical skills but differ in technical focus and work settings.

What are some common challenges faced by Remote Embedded Machine Learning Engineers, and how can they be addressed?

Remote Embedded Machine Learning Engineers often encounter challenges related to hardware access, debugging embedded devices remotely, and collaborating with cross-functional teams across time zones. To address these, it's important to set up robust remote development environments, use simulation tools when physical hardware isn't available, and establish clear communication channels for effective teamwork. Regular virtual meetings and detailed documentation also help ensure alignment and smooth progress, despite the remote nature of the work.
What are popular job titles related to Remote Embedded Machine Learning jobs in Colorado? For Remote Embedded Machine Learning jobs in Colorado, the most frequently searched job titles are:
What job categories do people searching Remote Embedded Machine Learning jobs in Colorado look for? The top searched job categories for Remote Embedded Machine Learning jobs in Colorado are:
Remote Embedded 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

Re-posted 3 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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