Pay
$166K–$240K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 1,279 postings in the last year. Stated ranges, not salaries paid.
Machine Learning Engineer
Cambridge, MA, United States
Open 4 months, first seen by us 125 days ago- Pay
- Pay not listedSimilar roles state $166K–$240K
- Work setting
On-site — work setting source
Work setup in the employer’s posting: On-site
From the employer’s 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
Full postingImplement and scale new deep learning architectures with researchers
Optimize and deploy the end-to-end machine learning pipeline
Develop software libraries and accelerators for neural network training on distributed systems
Write and maintain high-quality Python/C++ code
From the employer’s posting
Implementing and scaling new deep learning architectures in close collaboration with researchers.
End-to-end optimization and deployment of our machine learning pipeline.
Develop software libraries and accelerators for training neural networks interfacing with search and reinforcement learning algorithms on distributed systems.
Provide, maintain and optimize high-quality Python/C++ code.
What you’ll bring
All qualificationsCore experience
- Expert-level knowledge of PyTorch and distributed deep learning
- Proven ability to rapidly turn research papers into prototypes (industry or research labs experience)
- Experience designing, scaling and optimizing machine learning infrastructure
- Team-oriented and comfortable wearing multiple hats in a growing company
Qualification wording
Expert-level knowledge of PyTorch and distributed deep learning.
Proven ability to rapidly translate a research paper into prototypes (industry or research labs experience).
Experience designing, scaling, and optimizing machine learning infrastructure (e.g., distributed cloud computing, feature pipelines, visualization, MLOps, monitoring).
Team-oriented and comfortable wearing multiple hats in a growing company.
Posting record
Report an errorOpen 4 monthsWe first saw this posting 125 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
- Status in our records
- Live
- First seen by us
- Jul 3, 2026125 days ago
- Recorded sightings
- 45
- Last seen by us
- Nov 5, 2026
- Employer says posted
- May 2, 2021
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Time since we first saw it
Day 125
Up longer than most. Similar jobs usually come down between day 6 and day 70.
From 4,481 similar postings that came down. Coming down is not always a hire.
Common Sense Machines is hiring
2 open jobs
- No new data jobs since July
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
Where the posting names them
- Develop software libraries and accelerators for training neural networks interfacing with search and reinforcement learning algorithms on distributed systems. - Provide, maintain and optimize high-quality Python/C++ code. Qualifications
Qualifications - Expert-level knowledge of PyTorch and distributed deep learning. - Proven ability to rapidly translate a research paper into prototypes (industry or research labs experience).
Your next step
Complete your application on jobs.smartrecruiters.com. The employer’s form will show what is required.
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- Uploading your resume fills in the application form for you, so check what it filled before you send.
Already applied? Track this application
Has Common Sense Machines posted this job before?
Yes. We’ve followed one other Machine Learning Engineer job there since July 2026. It is still up.
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.
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
Job Description
We are looking for a machine learning engineer to train generative models on large scale datasets and compute infrastructure. You will be part of a small but growing team of engineers and scientists building 3D generative models to capture an unprecedented level of detail and diversity of physical objects. You will have a broad range of responsibilities including:
- Implementing and scaling new deep learning architectures in close collaboration with researchers.
- End-to-end optimization and deployment of our machine learning pipeline.
- Develop software libraries and accelerators for training neural networks interfacing with search and reinforcement learning algorithms on distributed systems.
- Provide, maintain and optimize high-quality Python/C++ code.
Qualifications
- Expert-level knowledge of PyTorch and distributed deep learning.
- Proven ability to rapidly translate a research paper into prototypes (industry or research labs experience).
- Experience designing, scaling, and optimizing machine learning infrastructure (e.g., distributed cloud computing, feature pipelines, visualization, MLOps, monitoring).
- Team-oriented and comfortable wearing multiple hats in a growing company.
Additional Information
We provide competitive compensation (cash and stock options), flexible work hours, unlimited vacation, and top-tier medical coverage. Our headquarters is in Cambridge, MA. Common Sense Machines is an equal opportunity employer and we are committed to creating a diverse and inclusive environment for all employees.
Company Description
Want to build general-purpose artificial intelligence for 3D perception and model building? Common Sense Machines is developing a platform that learns to translate the visual world into a 3D simulation for people and machines. We are a seed-stage venture-backed company founded by a group of PhDs and faculty from MIT. We have worked on large AI systems at DeepMind and have collectively founded three companies with successful exits.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Cambridge, MA, United States
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.