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Remote Embedded Machine Learning Jobs (NOW HIRING)

You will help design and build end-to-end machine learning solutions. * You will be working in ... This role is remote and the base pay range for a successful candidate is dependent on their ...

Remote We are seeking an Applied Machine Learning Engineer with a strong focus on practical solutions and software development (ability to work on both open-ended research problems and production ...

Machine learning: * Data pipelines: ingest data from physical systems, curate datasets, and convert ... embedded with a customer when it matters How we work at Rerun * We're a remote company ...

We're seeking a skilled Machine Learning Engineer to build and deploy production ML systems for the ... Onsite / Remote / Flexible work arrangements or hybrid options (position dependent) * Relocation ...

... devices/embedded systems. * White-box understanding of classical ML algorithms (SVMs, HMMs ... Proficiency in Unix-based environments (Linux, macOS) including working with remote servers and ...

Collaborate with Embedded Systems and Hardware teams to define device-side preprocessing and data ... Remote, US or Canada. NYC preferred. * Qualified applicants will receive consideration for ...

Remote Commitment: 40 hours/week Role Responsibilities * Guide research and engineering teams to close knowledge gaps in data science , AI , and machine learning domains. Surface nuances that ...

Senior Machine Learning Engineer

Detroit, MI · On-site +1

$126K - $180K/yr

... devices/embedded systems. * White-box understanding of classical ML algorithms (SVMs, HMMs ... Proficiency in Unix-based environments (Linux, macOS) including working with remote servers and ...

Vienna, VA and Chantilly, VA with remote flexibility Responsibilities: As a Machine Learning Engineer, you'll be part of the Agile team delivering machine learning applications and software systems ...

Vienna, VA and Chantilly, VA with remote flexibility Responsibilities: As a Machine Learning Engineer, you'll be part of the Agile team delivering machine learning applications and software systems ...

Machine Learning Engineer - Edge

Lowell, MA · On-site +1

$86K - $135K/yr

Machine Learning Engineer - Edge *Please consider before applying: This is a hybrid role, and ... Experience with embedded systems and hardware platforms. * Fundamentals of audio and speech signal ...

Machine Learning Engineer - Edge

Dover, NH · On-site +1

$86K - $135K/yr

Machine Learning Engineer - Edge *Please consider before applying: This is a hybrid role, and ... Experience with embedded systems and hardware platforms. * Fundamentals of audio and speech signal ...

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Remote Embedded Machine Learning information

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$70K

$153.4K

$174K

How much do remote embedded machine learning jobs pay per year?

As of May 30, 2026, the average yearly pay for remote embedded machine learning in the United States is $153,383.00, according to ZipRecruiter salary data. Most workers in this role earn between $131,500.00 and $173,000.00 per year, depending on experience, location, and employer.

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 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 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.

More about Remote Embedded Machine Learning jobs
What cities are hiring for Remote Embedded Machine Learning jobs? Cities with the most Remote Embedded Machine Learning job openings:
What are the most commonly searched types of Embedded Machine Learning jobs? The most popular types of Embedded Machine Learning jobs are:
What states have the most Remote Embedded Machine Learning jobs? States with the most job openings for Remote Embedded Machine Learning jobs include:
Infographic showing various Remote Embedded Machine Learning job openings in the United States as of May 2026, with employment types broken down into 16% Full Time, and 84% Part Time. Highlights an 94% Physical, and 6% Remote job distribution, with an average salary of $153,383 per year, or $73.7 per hour.
Machine Learning PhD Intern, Economics

Machine Learning PhD Intern, Economics

Instacart

Remote

$50/hr

Internship

This job post has expired today. Applications are no longer accepted.


Instacart rating

6.7

Company rating: 6.7 out of 10

Based on 29 frontline employees who took The Breakroom Quiz


Job description

We're transforming the grocery industry
At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers.
Instacart has become a lifeline for millions of people, and we're building the team to help push our shopping cart forward. If you're ready to do the best work of your life, come join our table.
Instacart is a Flex First team
There's no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work-whether it's from home, an office, or your favorite coffee shop-while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work.
Overview
We are looking for interns to join Instacart's Economics team. The ideal candidate for this role will bring a combination of experience in both economics and machine learning. We are in particular looking for current or recently graduated PhD students in economics or related fields like marketing, finance, or operations research. Candidates should bring some relevant research experience, typically in computationally intensive empirical topics, as well as some exposure to machine learning coursework and applications.
The Economics team at Instacart works on a range of interesting and challenging problems at the intersection of machine learning and economics, from aligning the incentives in our multi-sided marketplace to analyzing the impact of behavioral nudges on our customers' and shoppers' decisions. Some of the core areas of focus for our team include online advertising, uplift and long term value modeling, logistics, marketplace optimization (consumers, shoppers, retailers), inventory intelligence, and general causal inference. You can find more information in our blog post that introduces the team and the type of work we do.
About the Job
  • You will help design and build end-to-end machine learning solutions.
  • You will be working in small and cross-functional product teams, with great opportunities for growth and ownership of projects.
  • You will be an active member of an internal community, including economists, data scientists, operations research scientists and machine learning engineers, sharing learnings, best practices and research across many domains.
  • You will develop high impact solutions to support Instacart's ambitious growth plans.
  • You will work closely with engineers, product managers, other teams, and both internal and external stakeholders, owning a large part of the process from problem understanding to recommending a solution and testing it in controlled experiments.
  • You will have the freedom to suggest and drive organization-wide initiatives.

About You
Minimum Qualifications
  • Current or recently graduated PhD student in economics or a related field with focus on data-intense problems.
  • A blend of economic theory, applied econometrics, and business acumen that let you jump into a fast-paced environment and contribute from day one.
  • Expertise in causal inference with observational and experimental data.
  • Expertise in Python or R and fluency in data manipulation (SQL, Pandas) and machine learning (scikit-learn, XGBoost, Keras/Tensorflow) tools.
  • Self-motivation and a strong sense of ownership

Instacart provides highly market-competitive compensation and benefits in each location where our employees work. This role is remote and the base pay range for a successful candidate is dependent on their permanent work location. Please review our Flex First remote work policy here.
Offers may vary based on many factors, such as candidate experience and skills required for the role. Please read more about our benefits offeringshere.
For US based candidates, the base pay ranges for a successful candidate are listed below.
CA, NY, CT, NJ
$50-$50 USD
WA
$48-$48 USD
OR, DE, ME, MA, MD, NH, RI, VT, DC, PA, VA, CO, TX, IL, HI
$44-$44 USD
All other states
$42-$42 USD

What Instacart employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


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About Instacart

Sourced by ZipRecruiter

Instacart, based in San Francisco, CA, US, operates within the retail industry, specifically grocery delivery and pick-up service. It is recognized as a pioneer in this field, delivering fresh groceries from local stores directly to customers' doors. The company, which launched its services in 2012, continues to pioneer change in the online grocery shopping sector through its commitment to cutting-edge technology, new business ideas, and dedicated service.

Industry

Technology, communication and media

Company size

10,000+ Employees

Headquarters location

San Francisco, CA, US

Year founded

2012