Time since we first saw it
Day 12
Similar jobs usually come down between day 7 and day 72.
From 4,777 similar postings that came down. Coming down is not always a hire.
Location not stated
Actively hiring, first seen by us 12 days agoDevelop and evaluate machine learning algorithms to improve product and system performance
Translate algorithms and technical specifications into code, then test and debug
Lead technical teams and break challenging projects into executable sprints
Drive code reviews to follow DevSecOps and MLOps best practices
Integrate external vendor and partner technology into the team's autonomy stack
uses machine language and statistical modeling techniques to include but not limited to decision trees, logistic regression, Bayesian analysis and others to develop and evaluate algorithms
uses programming language and technologies to translate algorithms and technical specifications into code
Lead technical teams and scope challenging projects into executable sprints.
Drive code reviews to help team adhere to general DevSecOps and MLOps best practices.
Interface with external vendors and partners to integrate their technology into the team’s autonomy stack.
Actively hiringFirst seen by us 12 days ago, still listed, and not a repost of an earlier posting.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 12
Similar jobs usually come down between day 7 and day 72.
From 4,777 similar postings that came down. Coming down is not always a hire.
4 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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New ML Engineer postings at the employers we follow are up 13% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 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.
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.
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.
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