Machine Learning / AI Engineer

United States, Work from Home

Actively hiring, first seen by us 3 days ago

Pay: $115,000–158,200/yearAnnual period assumed. Location-specific pay — pay source
Emerging AI technologies and AI-assisted engineering tools. At Bose, you're inspired to be and do your best and are rewarded for your unique talents! Our compensation is thoughtfully tailored to your skills, experience, education, and location, and goes beyond base salary. The hiring range for this position in the primary work location of Remote, Massachusetts is: $115,000-$158,200.The hiring range for other Bose work locations may vary.

In addition to competitive base pay we offer rewards including bonus programs, comprehensive health and welfare benefits, a 401(k) plan, plus exclusive perks designed to support your wellbeing, and a generous employee discount where you can immerse yourself in our products and experiences. We are a proudly independent company—driven by purpose, guided by our values, and united by a belief in the power of sound. As the world leader in audio experiences, we’re creating what’s next—pushing boundaries and delivering transformative sound experiences for people everywhere. Join us and make your next career move a mic-drop. Let’s Make Waves.‎
Read the full posting
Work setting: Remote — work setting source
Listed location: United States, Work from Home
Read the full posting
Employment: Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting

What you’ll work on

You’ll help design, train, test, and optimize machine learning models, with a focus on making AI work efficiently on devices with limited memory and computing power.

You’ll collaborate with engineers across machine learning, software, embedded systems, and hardware.

Develop, train, and evaluate ML models for consumer audio applications
Reduce model latency, memory use, and computational demands while keeping accuracy
Partner with software, embedded, and hardware engineers to put AI on devices
Analyze results, debug issues, and guide next experiments with testing

From the employer’s posting

You’ll help design, train, test, and optimize machine learning models, with a focus on making AI work efficiently on devices with limited memory and computing power. This work brings together Efficient AI and Edge ML: building models that deliver strong results within the constraints of real products.

You’ll collaborate with engineers across machine learning, software, embedded systems, and hardware. Along the way, you’ll deepen your technical expertise, contribute your ideas, and learn how models move from experimentation toward deployment.

Develop, train, and evaluate machine learning models for consumer audio applications.

Explore ways to improve accuracy while reducing latency, memory use, and computational demands.

Partner with software, embedded, and hardware engineers to help bring AI capabilities onto devices.

Analyze results, debug issues, and use testing to guide your next experiment.

What you’ll bring

All qualifications

Core experience

Bachelor's or advanced degree in CS, EE, ML, or a related technical field
Solid foundation in machine learning and deep learning with hands-on model building
Proficiency in Python and a framework such as PyTorch or TensorFlow

Qualification wording

A bachelor’s or advanced degree in Computer Science, Electrical Engineering, Machine Learning, or a related technical field.

A solid foundation in machine learning and deep learning, with hands-on experience building and evaluating models.

Proficiency in Python and experience with a framework such as PyTorch or TensorFlow.

Education & alternatives

What You’ll Bring - A bachelor’s or advanced degree in Computer Science, Electrical Engineering, Machine Learning, or a related technical field. - 3+ years of relevant machine learning or AI experience, which may include applicable research or substantial project work.

Apply at Boseallaboutme

Posting record

Report an error

Actively hiringFirst seen by us 3 days ago, still listed, and not a repost of an earlier posting.

Status in our records: Live
First seen by us: Nov 3, 20263 days ago
Recorded sightings: 4
Last seen by us: Nov 6, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

$166K–$240K is typical

The middle half of what similar US postings state. This one doesn’t list pay.

From 1,319 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 3

Early. Similar jobs usually come down between day 6 and day 71.

At Boseallaboutme, jobs usually come down by about day 19.

From 4,626 similar postings that came down, and 9 of Boseallaboutme’s. Coming down is not always a hire.

Boseallaboutme is hiring

9 open jobs

Open jobs by the week we first saw them, last 12 weeks.

ML Engineer hiring is picking up
Takes jobs down quickly

Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

C
Python
PyTorch
TensorFlow
C++

Where the posting names them

- Edge ML, embedded AI, or deploying models on devices with limited computing resources. - C/C++ or deployment tools such as ONNX or TensorFlow Lite. - Audio ML, speech processing, acoustic sensing, or related applications.

- A solid foundation in machine learning and deep learning, with hands-on experience building and evaluating models. - Proficiency in Python and experience with a framework such as PyTorch or TensorFlow. - Experience training, evaluating, and debugging models—and curiosity about how to make them better.

Upload resume Add LinkedIn

Your next step

Complete your application on boseallaboutme.wd503.myworkdayjobs.com. The employer’s form will show what is required.

Applying through Workday

You create an account with each employer before you can upload anything. Every Workday employer has its own account, so one sign-up doesn’t carry over.
“Autofill with Resume” comes right after sign-in, before the My Information and My Experience steps. Check every field it fills in those steps, since that’s what recruiters see.
Your application status lives in that employer’s Candidate Home, under the same sign-in.

Already applied? Track this application

Demand for ML Engineer roles

New ML Engineer postings at the employers we follow are up 12% over the last 5 weeks compared with the 5 before.

August 17Last week

Each bar is one week of new postings. The darkest bars are the last 5 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under ML Engineer, by the work the posting describes.

ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.

Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.

A data scientist often works out which model to build; an ML engineer makes it run reliably in production.

US government figures for computer and information research scientists

Median yearly pay, May 2025: $140,300
Expected change, 2025 to 2035: 21.8% more jobsagainst 3.5% for all jobs

The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.

Job description

View original posting ↗

At Bose Corporation, we believe sound is the most powerful force on earth — and for over 60 years, we have been a company built on innovation, excellence, and independence. Privately owned, fiercely customer-focused, and driven by our values, we continue to lead industries and transform lives through sound.

Today, Bose Corporation is entering an exciting new era. Across multiple global Business Units and Global Functions, we are shaping the future of audio technology, automotive, luxury, and premium experiences. We invite you to join us in this transformation.

Job Description

Build AI that people can hear and experience.

At Bose, we believe sound is the most powerful force on earth. As a Machine Learning / AI Engineer, you’ll help bring that belief to life - developing intelligent capabilities for the next generation of audio experiences.

If you enjoy experimenting with models, solving practical problems, and turning ideas into working technology, this is an opportunity to grow your skills while contributing to products and technology that people use every day.

About the Role

You’ll help design, train, test, and optimize machine learning models, with a focus on making AI work efficiently on devices with limited memory and computing power. This work brings together Efficient AI and Edge ML: building models that deliver strong results within the constraints of real products.

You’ll collaborate with engineers across machine learning, software, embedded systems, and hardware. Along the way, you’ll deepen your technical expertise, contribute your ideas, and learn how models move from experimentation toward deployment.

What You’ll Do

Build and experiment. Develop, train, and evaluate machine learning models for consumer audio applications.
Make models more efficient. Explore ways to improve accuracy while reducing latency, memory use, and computational demands.
Connect models to products. Partner with software, embedded, and hardware engineers to help bring AI capabilities onto devices.
Investigate and improve. Analyze results, debug issues, and use testing to guide your next experiment.
Learn and contribute. Explore emerging ML techniques, share what you discover, and bring fresh ideas to the team.

What You’ll Bring

A bachelor’s or advanced degree in Computer Science, Electrical Engineering, Machine Learning, or a related technical field.
3+ years of relevant machine learning or AI experience, which may include applicable research or substantial project work.
A solid foundation in machine learning and deep learning, with hands-on experience building and evaluating models.
Proficiency in Python and experience with a framework such as PyTorch or TensorFlow.
Experience training, evaluating, and debugging models—and curiosity about how to make them better.
An analytical approach to problem-solving, a willingness to ask questions, and enthusiasm for working with others.

Experience That Can Help You Stand Out

You don’t need experience in every area below. We’re interested in the strengths you bring and what you’re excited to learn.

Techniques such as quantization, pruning, or model compression.
Edge ML, embedded AI, or deploying models on devices with limited computing resources.
C/C++ or deployment tools such as ONNX or TensorFlow Lite.
Audio ML, speech processing, acoustic sensing, or related applications.
Emerging AI technologies and AI-assisted engineering tools.

At Bose, you're inspired to be and do your best and are rewarded for your unique talents! Our compensation is thoughtfully tailored to your skills, experience, education, and location, and goes beyond base salary. The hiring range for this position in the primary work location of Remote, Massachusetts is: $115,000-$158,200.The hiring range for other Bose work locations may vary.

In addition to competitive base pay we offer rewards including bonus programs, comprehensive health and welfare benefits, a 401(k) plan, plus exclusive perks designed to support your wellbeing, and a generous employee discount where you can immerse yourself in our products and experiences. We are a proudly independent company—driven by purpose, guided by our values, and united by a belief in the power of sound. As the world leader in audio experiences, we’re creating what’s next—pushing boundaries and delivering transformative sound experiences for people everywhere. Join us and make your next career move a mic-drop. Let’s Make Waves.

‎

Source details