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Remote Embedded Machine Learning Jobs in Minnesota

$44.25 - $60.50/hr

Machine Learning Operations Engineers enable development end-to-end data science applications that ... Ability to work in a collaborative, remote development environment. * Skilled in communicating ...

Lead Research Engineer

Eagan, MN · On-site +1

$104K - $137K/yr

... remote teams. * Be an Agile Person:With a strong sense of urgency and a desire to work in a fast ... Experienceintegrating Machine Learning solutionsinto production-grade softwarewith a sound ...

Innovation Exposure - Contribute to initiatives involving analytics, machine learning, natural language processing, data architecture, and decision modeling * Remote Flexibility - Enjoy the benefits ...

A specialization in machine-learning, artificial intelligence, cognitive science or data science is ... Opportunity for a hybrid work arrangement combining remote and in-office work. The specific ...

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Remote Embedded Machine Learning information

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

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 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 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 the most commonly searched types of Embedded Machine Learning jobs in Minnesota?

The most popular types of Embedded Machine Learning jobs in Minnesota are:

What are popular job titles related to Remote Embedded Machine Learning jobs in Minnesota?

For Remote Embedded Machine Learning jobs in Minnesota, the most frequently searched job titles are:

What job categories do people searching Remote Embedded Machine Learning jobs in Minnesota look for?

The top searched job categories for Remote Embedded Machine Learning jobs in Minnesota are:

What cities in Minnesota are hiring for Remote Embedded Machine Learning jobs?

Cities in Minnesota with the most Remote Embedded Machine Learning job openings:

Machine Learning Operations Engineer

On-site, Remote


Intermountain Health

7.2

Company rating: 7.2 out of 10

Based on 846 frontline employees who took The Breakroom Quiz

345th of 894 rated healthcare providers

People enjoy working here

Good employer

Recommended by students


$44.25 - $60.50/hr

Full-time

This job post has expired 4 days ago. Applications are no longer accepted.


Job description

Job Description:
Machine Learning Operations Engineers enable development end-to-end data science applications that apply predictive, prescriptive, and cognitive analytic methods to system-wide clinical and operational strategic initiatives and analytics products that serve both internal and external customers. Using industry leading data science and artificial intelligence (AI) practices to deliver on our mission to accelerate the transition from volume to value-based systems of care, improve outcomes, and make costs more affordable. Machine Learning Ops Engineers are responsible for working closely with our data scientists, data architects / engineers, and software engineers to build and deploy machine learning solutions that solve real-world problems in the healthcare industry.
We are committed to offering flexible work options where approved and stated in the job posting. However, we are currently not considering candidates who reside or plan to reside in the following states: California, Connecticut, Hawaii, Illinois, Maine, Massachusetts, Minnesota, New York, Pennsylvania, Rhode Island, Virginia, Vermont, Washington.
Please note that a video interview through Microsoft Teams will be required as well as potential onsite interviews and meetings
Job Essentials
Machine Learning Operational Engineers develop machine learning engineering frameworks to enable governance, testing, and automation using best practices in continuous integration and continuous delivery. They build and deploy machine learning platforms leveraging model registries, feature stores, model monitoring, etc. and operationalize and optimize data science models to ensure reliability, scalability, and maximum performance. They automate the retraining, maintenance, and monitoring of models in production, ensure data science models follow best practices in Responsible AI and stay up to date with the latest machine learning technologies and techniques.
The Senior level Machine Learning Operations Engineer works on projects that are highly complex in nature, needing subject matter expertise and experience to perform successfully. This position may serve as a subject matter expert and resource for others and will deploy and maintain innovative data science tools and methods that result in products or strategic insights with significant return on investment while meeting project requirements and timelines. Develops efficient and scalable machine learning systems that enable integration of data
science applications into healthcare operations, strategy, value improvement, care advancement, patient safety and satisfaction. Partners with data scientists, application developers, data architects, and system engineers to recommend and develop ML systems and pipelines and quickly learns and appropriately applies cutting edge advanced analytic methodologies and tools in creative and novel ways. The Senior level also directs and pilots initiatives from inception to workflow integration, including engaging stake holders, analytics, data science, data architecture / engineering, and software engineering teams.
Skills
  • AI/ML modeling techniques
  • MLOps platforms
  • Programming languages
  • DevOps practices
  • Data manipulation
  • Cloud Computing
  • Responsible AI Processing and Monitoring

Minimum Qualifications:
  • Experience leading the development of MLOps machine learning platforms leveraging model registries, feature stores, model monitoring, etc.
  • Successful experience leading the development, implementation, and administration of machine learning systems and pipelines within operational workflows from end-to-end.
  • Experience utilizing and creating custom API's, functions, libraries, and/or packages in multiple programming languages.
  • Advanced experience programming and reviewing code using statistical and data software tools like Python, R, Java, Scala, etc.
  • Experience with Linux and bash scripting.
  • Advanced experience with DevOps best practices (continuous integration and continuous deployment) and tools (such as Docker, Kubernetes, and Git).
  • Advanced experience writing and tuning queries to manipulate and combine large or complex data sets, including unstructured data sources.
  • Experience using Big Data technologies like Hadoop, Spark, Hive, NoSQL, in-memory data stores, etc., and Cloud technologies such as AWS, Azure, etc.
  • Ability to work in a collaborative, remote development environment.
  • Skilled in communicating technical insights through data visualization, verbal, written, and interpersonal communication.
  • Experience fostering machine learning partnerships across all levels of an organization through effective communication and relationship management

Preferred Qualifications:
  • Degree earned in a related field such as data science, computer science, engineering, information systems, or other quantitative and computational discipline.
  • Experience using Azure or AWS cloud computing and Databricks.
  • Successful experience working in a healthcare or insurance setting.

Physical Requirements
Interact with others by effectively communicating, both orally and in writing
Operate computers and other office equipment requiring the ability to move fingers and hands
See and read computer monitors and documents
Remain sitting or standing for long periods of time to perform work on a computer, telephone, or other equipment
May require lifting and transporting objects and office supplies, bending, kneeling and reaching
Location:
Key Bank Tower
Work City:
Salt Lake City
Work State:
Utah
Scheduled Weekly Hours:
40
The hourly range for this position is listed below. Actual hourly rate dependent upon experience.
$60.67 - $95.52
We care about your well-being - mind, body, and spirit - which is why we provide our caregivers a generous benefits package that covers a wide range of programs to foster a sustainable culture of wellness that encompasses living healthy, happy, secure, connected, and engaged.
Learn more about our comprehensive benefits package here.
By applying for a position with Intermountain, I acknowledge that I will comply with all applicable Intermountain policies and expectations. If applying for a remote or hybrid role, this includes remote work expectations related to confidentiality, information security, work schedules, conflicts of interest, and use of company equipment. I further acknowledge that outside employment or activities may not interfere with job responsibilities or create a conflict of interest with Intermountain. Actual or reasonably perceived conflicts may be grounds for disqualification from consideration or, if hired, corrective action up to and including termination of employment.
Intermountain Health is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability or protected veteran status.
At Intermountain Health, we use the artificial intelligence ("AI") platform, HiredScore to improve your job application experience. HiredScore helps match your skills and experiences to the best jobs for you. While HiredScore assists in reviewing applications, all final decisions are made by Intermountain personnel to ensure fairness. We protect your privacy and follow strict data protection rules. Your information is safe and used only for recruitment. Thank you for considering a career with us and experiencing our AI-enhanced recruitment process.
All positions subject to close without notice.

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