Hands-on experience with CI/CD pipelines, automation tools, and version control systems like Azure DevOps, Github, or similar and strong understanding of machine learning concepts and the ML ...
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Machine Learning Engineer
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Machine Learning Engineer
Niles, IL · On-site
$103K - $129K/yr
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Senior Machine Learning Engineer
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Senior Machine Learning Engineer Remote in US $160,000 - $190,000 Base + 10% Bonus THE COMPANY Harnham is partnering with a fintech that has built a leading fraud protection platform enabling ...
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Principal Machine Learning Engineers at Thoughtworks use modern architectures to develop end-to-end scalable machine learning systems and applications. They use their specialized depth and breadth of ...
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Machine Learning Engineer
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Machine Learning Engineer
$53 - $72.75/hr
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Machine Learning Engineer
$53 - $72.75/hr
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Machine Learning Engineer
$53 - $72.75/hr
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Machine Learning Engineer
Chicago, IL · On-site
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Chicago, IL · On-site
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Chicago, IL · On-site
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Machine Learning Engineer Niles, Illinois
Niles, IL · On-site
$103K - $129K/yr
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Machine Learning Engineer
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AWS Machine Learning Engineer
Chicago, IL · On-site
$72K - $108K/yr
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Principal Machine Learning Engineer
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Principal Machine Learning Engineer
Chicago, IL · On-site
$200K - $250K/yr
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Principal Machine Learning Engineer
Chicago, IL · On-site
$200K - $250K/yr
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Principal Machine Learning Engineer
Chicago, IL · On-site
$200K - $250K/yr
We're looking for a Principal Machine Learning Engineer to help shape the next phase of our platform - influencing architecture, driving best practices, and solving high-leverage problems. You'll ...
Principal Machine Learning Engineer
Chicago, IL · On-site
$200K - $250K/yr
We're looking for a Principal Machine Learning Engineer to help shape the next phase of our platform - influencing architecture, driving best practices, and solving high-leverage problems. You'll ...
As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...
As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...
Machine Learning Engineer information
See Barrington, IL salary details
$31.3K - $46K
1% of jobs
$46K - $60.6K
1% of jobs
$60.6K - $75.3K
5% of jobs
$75.3K - $89.9K
6% of jobs
$102K is the 25th percentile. Wages below this are outliers.
$89.9K - $104.6K
14% of jobs
$104.6K - $119.2K
14% of jobs
The median wage is $126.5K / yr.
$119.2K - $133.9K
18% of jobs
$133.9K - $148.5K
14% of jobs
$151.5K is the 75th percentile. Wages above this are outliers.
$148.5K - $163.2K
12% of jobs
$163.2K - $177.8K
11% of jobs
$177.8K - $192.5K
5% of jobs
$31.3K
$128.1K
$192.5K
How much do machine learning engineer jobs pay per year?
Is ML full of coding?
What engineers make $500,000?
What do machine learning engineers do?
What are Machine Learning Engineers?
What are the key skills and qualifications needed to thrive as a Machine Learning Engineer, and why are they important?
Which 5 jobs will survive AI?
What Does a Machine Learning Engineer Do?
A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.
What are some common challenges faced by Machine Learning Engineers when deploying models to production?
What is the difference between Machine Learning Engineer vs Data Scientist?
| Aspect | Machine Learning Engineer | Data Scientist |
|---|---|---|
| Credentials | Bachelor's or Master's in CS, Data Science, or related; experience with ML frameworks | Bachelor's or Master's in Statistics, Data Science, or related; strong analytical skills |
| Work Environment | Develops scalable ML models, deploys algorithms into production | Analyzes data, builds models, interprets data insights |
| Industry Usage | Tech companies, startups, AI-focused firms | Finance, healthcare, marketing, research organizations |
While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

Full-time
Posted 10 days ago
Job description
Position Responsibilities:Â
- Design, build, and maintain Continuous Integration/Continuous Development (CI/CD) pipelines for machine learning modelsÂ
- Deploy and manage ML models in production environments using containerization and orchestration technologiesÂ
- Implement monitoring, logging, and alerting solutions to track model performance, system health, and data driftÂ
- Collaborate with data scientists to understand model requirements and optimize the process of transforming models from development to a production-ready stateÂ
- Create and maintain technical documentation for ML Operations (Ops) processes, infrastructure, and deploymentsÂ
- Define ML/Artificial Intelligence (AI) governance to ensure data security and ethical standards are met for all modeling processesÂ
- Travel up to 5% of the timeÂ
- Other duties as assigned Â
Required Education and Experience:Â
- Bachelor's degree in computer science, Data Science, Mathematics, or related quantitative discipline and 3 to 5 plus years of experience in ML Engineering, Software Engineering, or a related field or High School Diploma/General Education Diploma and 7 plus years of the above stated experienceÂ
Preferred Education and Experience:Â
- Master's Degree in computer science, Data Science, or other graduate education in related quantitative fieldsÂ
- Hands-on experience with CI/CD pipelines, automation tools, and version control systems like Azure DevOps, Github, or similar and strong understanding of machine learning concepts and the ML development lifecycleÂ
- Experience building ML Ops infrastructure and serving models via cloud platforms such as Azure, Amazon Web Services (AWS), or Google Cloud Platform (GCP)Â
- Strong proficiency in Python and working knowledge of Bash/shell scripting for automation and system operationsÂ
- Strong understanding of Structured Query Language (SQL) and experience with big data platforms, i.e., Snowflake, Databricks, or similarÂ
- Experience with Infrastructure-as-Code tools, i.e., Terraform, Azure Resource Manager, or similar