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Remote Embedded Machine Learning Jobs in Michigan

Software Engineer, On Device

Ann Arbor, MI · On-site +1

$120K - $150K/yr

This edge software includes machine learning, optimization algorithms, and components that host ... for embedded systems, and deployment in real-world, intermittently connected environments

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 ...

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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 Michigan? The most popular types of Embedded Machine Learning jobs in Michigan are:
What cities in Michigan are hiring for Remote Embedded Machine Learning jobs? Cities in Michigan with the most Remote Embedded Machine Learning job openings:
Software Engineer, On Device

Software Engineer, On Device

Utilidata

Ann Arbor, MI • On-site, Remote

$120K - $150K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 16 days ago


Job description

Utilidata is a fast-growing NVIDIA-backed AI company enabling AI data centers to dynamically orchestrate power and unlock more compute capacity from existing energy infrastructure. For over a decade, we have applied AI to the electric grid - bringing real-time visibility and power-flow control to complex energy infrastructure. Our Karman platform, built on a custom NVIDIA module, brings that same capability to AI data centers, giving operators a way to better use the power already available to them.
We are expanding our engineering team and looking for a Software Engineer to support the productionalization of our IoT platform, with a primary emphasis on the software that runs on edge IoT devices. This edge software includes machine learning, optimization algorithms, and components that host these capabilities that must meet high standards of performance, security, reliability, and accuracy. We are looking for candidates who are mission-driven, collaborative, adaptive and experienced in designing, writing, testing, and debugging distributed enterprise software at scale. Ideal candidates will possess knowledge of Python, Linux, continuous integration and deployment (CI/CD), with direct experience designing and developing successful enterprise software.
Responsibilities
  • Design, propose, plan, implement, and test resource-constrained, edge software in Python (and possibly lower-level languages, e.g., Rust) including the implementation of precision telemetry collection, real-time control interfaces, and robust system observability
  • Create and maintain CI/CD processes as necessary to support development and deployment with a focus on reproducibility, regression testing for embedded systems, and deployment in real-world, intermittently connected environments
  • Contribute to internal and external technical documentation
  • Collaborate with a cross-functional team of software, hardware, quality assurance (QA), and power systems engineers; data scientists; and leadership
  • Provide high-quality, in-depth code and architecture reviews, implement new features, and provide technical leadership while coordinating with project management, QA, and other internal teams
  • Continually advocate for and implement process improvement and automation
  • Foster a culture of open communication, innovation, and continual improvement
  • Mentor other engineers using paired programming, code review, and collaborative test scenario design
Minimum Qualifications
  • 5+ years of professional experience including 3+ years of experience developing production software and systems, or a combination of educational and professional experience commensurate with this level of experience
  • Demonstrated ability to design and implement distributed systems utilizing microservices in a resource-constrained environment (edge devices with limited memory, CPUs, GPU capacity, etc.)
  • Extensive experience using Python, C/C++, Rust, and the Linux operating system
  • Experience with device layered security, i.e. encryption (PKI) , disk partitioning, secure boot, os kernel libraries, device drivers, os processes/daemons
  • Data compression and schema management for device time series data
  • Experience implementing and maintaining CI/CD workflows (e.g., GitHub Actions or Jenkins)
  • Strong understanding of synchronous and asynchronous network communication, including REST APIs, gRPC, binary protocols, and distributed publish/subscribe messaging systems and protocols like MQTT and ZeroMQ
  • Strong written and oral communication skills, with a proven track record of working effectively both individually and as part of a team
Enhanced Qualifications (Nice to Have)
  • Experience designing, building and deploying applications and reusable libraries based on the NVIDIA ML software stack on the Jetson Platform
  • Experience with system integration testing including HIL and SIL
  • Understanding of SQL/NoSQL Database implementations (SQLite, Redis, Postgres, etc)
  • Well-versed in Docker/containerization
  • Hands-on knowledge of cloud platforms and services focused on IoT device management, security and OTA updates (AWS, Azure) preferably in the scale of million devices including managing release/versioning strategies and monitoring fleet-wide performance metrics
  • Experience with control systems applications (e.g. industrial processes, manufacturing, commercial buildings, SCADA) and/or power systems
  • Experience working with software and systems deployed in modern data center environments, including telemetry ingestion, rack-level integration, and coordination with orchestration platforms
  • Experience with Shell scripting, helm charts, ansible, and prometheus tools
Salary Range: $120,000 to $150,000 base compensation depending on experience and stock options. Salary will be commensurate with an individual's skills, training, years of experience, and in line with internal compensation bands.
Location: This position is based onsite at our company headquarters in Ann Arbor, Michigan, with flexibility for occasional remote work.
Our Commitments:
Utilidata values the diversity of our team. We provide equal employment opportunities without regard to race, color, religion, creed, sex, gender, sexual orientation, gender identity or expression, national origin, age, physical disability, mental disability, medical condition, pregnancy or childbirth, sexual orientation, genetics, genetic information, marital status, or status as a covered veteran or any other basis protected by applicable federal, state and local laws.
We are committed to:
  • Creating a diverse and inclusive workplace that is welcoming, supportive, affirming and respectful
  • Empowering employees to solve problems and work together to make a difference
  • Providing mentorship and growth opportunities as part of a collaborative team
  • A flexible work environment with flexible paid time off
  • Competitive compensation and benefits, including health, dental, vision, and employer-match 401k