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Remote Embedded Machine Learning Jobs in Wisconsin

$171K - $210K/yr

Data Engineering, Data Science or Machine Learning * Operations, Security and Data Governance ... Employee Resource Groups EEO/VEVRAA #LI-MH2 #LI-Remote

Implementation Engineer

Madison, WI ยท On-site +1

$80K - $85K/yr

Using AI and machine learning, our software analyzes billions of data points collected from sensors ... Hybrid/Remote Company - we are a company with hybrid and remote options. That being said, we have ...

Senior React Native Developer

Green Bay, WI ยท Remote

$53 - $70/hr

This role requires constant learning and a growth mindset. This is a remote role embedded with an ... Live AI-assisted interview You'll drive on your own machine/setup/config while pairing with an ...

This role can be remote in the United States and supports the Motion Drive Products Division in New ... Our Team Dynamics Our teams support each other, collaborate, and never stop learning. Everyone ...

This role can be remote in the United States and supports the Motion Drive Products Division in New ... Our Team Dynamics Our teams support each other, collaborate, and never stop learning. Everyone ...

This role can be remote in the United States and supports the Motion Drive Products Division in New ... Our Team Dynamics Our teams support each other, collaborate, and never stop learning. Everyone ...

Optimize our outbound/inbound machine. Define ICP audiences, craft messaging, and iterate based on ... Learning & development budget to invest in your growth * Remote-first culture with the autonomy to ...

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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 the most commonly searched types of Embedded Machine Learning jobs in Wisconsin? The most popular types of Embedded Machine Learning jobs in Wisconsin are:
What cities in Wisconsin are hiring for Remote Embedded Machine Learning jobs? Cities in Wisconsin with the most Remote Embedded Machine Learning job openings:
Security Engineer

Security Engineer

Northwinds Technology Solutions

Stevens Point, WI โ€ข Remote

Full-time

Posted 18 days ago


Job description

General Description

The Security Engineer plays a key role in protecting NorthWinds Technology Solutions, its affiliated companies, and its clients by designing, implementing, and maintaining enterprise security solutions. This position focuses heavily on the Microsoft security ecosystem, including endpoint protection, identity security, and related capabilities.

This role is responsible for strengthening the organizationโ€™s security posture through proactive monitoring, detection, and response, while working cross-functionally with infrastructure, cloud, and application teams. The Security Engineer will also participate in vulnerability management, incident response, and the ongoing evolution of security architecture and controls.

Core Responsibilities

Security Operations & Monitoring

  • Monitor, investigate, and respond to security alerts across Microsoft security and other platforms (Purview, Defender suite, SIEM, Entra ID)
  • Analyze logs and telemetry to identify suspicious activities and potential threats
  • Support incident response activities, including containment, eradication, and root cause analysis
  • Maintain and improve detection rules, analytics, and alert tuning

Microsoft Security Platform

Administer and Optimize:

  • Microsoft Defender for Endpoint, Identity, Cloud Apps, and Office 365
  • Microsoft Entra ID (Azure AD) security controls and tools
  • Microsoft Purview controls and tools

Additional responsibilities:

  • Develop and maintain automated workflows and playbooks
  • Integrate Microsoft security tools with other enterprise systems

Vulnerability & Risk Management

  • Conduct vulnerability assessments and coordinate remediation efforts
  • Partner with infrastructure and application teams to prioritize and mitigate risks
  • Contribute to risk tracking, reporting, and audit readiness (SOC 2, HIPAA, etc.)

Architecture & Engineering

  • Work with the Security Architect to identify and recommend improvements to enterprise security architecture
  • Assist with the implementation of security controls across cloud (Azure/AWS) and on-premises environments
  • Support identity and access management initiatives, including MFA, conditional access, and least privilege

Compliance & Governance

  • Assist with audits, security reviews, and third-party assessments
  • Ensure alignment with organizational security policies and regulatory requirements
  • Provide input into security standards, procedures, and documentation

Collaboration & Enablement

  • Work closely with infrastructure, network, and application teams to embed security controls
  • Provide technical guidance and support for security best practices
  • Help drive security awareness across engineering teams

Key Skills

  • Identity and access management (IAM)
  • Network security fundamentals (TCP/IP, firewalls, segmentation, switching, and routing)
  • Windows and cloud security principles
  • SIEM platforms and operations
  • Experience with vulnerability management and remediation processes
  • Familiarity with security frameworks and compliance standards (SOC 2, HIPAA, NIST, CIS)
  • AWS networking, security configuration, and tools
  • Strong analytical, troubleshooting, and problem-solving skills
  • Linux terminal and PowerShell experience
  • Copilot administration and machine learning familiarity
  • Effective communication and collaboration skills

Key Characteristics

  • Detail-oriented and proactive in identifying and mitigating risks
  • Strong ownership mindset with the ability to drive security initiatives forward
  • Collaborative, team-first approach across infrastructure and security functions
  • Continuous learner who stays up to date on evolving threats and technologies

Required Qualifications

  • 3โ€“5 years of experience in cybersecurity, security engineering, or security operations
  • Hands-on experience with Microsoft security technologies, including:
    • Microsoft Defender suite (Endpoint, Identity, Cloud Apps, Office 365)
    • Microsoft Entra ID (Azure AD) security features and Intune administration
  • Experience with endpoint detection and response (EDR/XDR) and SIEM platforms

Preferred Qualifications

  • Microsoft certifications (SC-200, SC-300, AZ-500, or equivalent)
  • Experience with automation and scripting (PowerShell, Python)
  • Exposure to cloud security (Azure and/or AWS)
  • Experience implementing conditional access policies and Zero Trust principles
  • Knowledge of threat intelligence and detection engineering

Work Conditions

  • Participation in an on-call rotation may be required
  • Primarily remote work environment
  • Limited travel (<5%)