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Machine Learning Engineer information
See Denton, TX salary details
$29.5K - $43.3K
1% of jobs
$43.3K - $57.2K
1% of jobs
$57.2K - $71K
5% of jobs
$71K - $84.8K
6% of jobs
$96.2K is the 25th percentile. Wages below this are outliers.
$84.8K - $98.6K
14% of jobs
$98.6K - $112.4K
14% of jobs
The median wage is $119.3K / yr.
$112.4K - $126.2K
18% of jobs
$126.2K - $140K
14% of jobs
$142.8K is the 75th percentile. Wages above this are outliers.
$140K - $153.8K
12% of jobs
$153.8K - $167.6K
11% of jobs
$167.6K - $181.4K
5% of jobs
$29.5K
$120.7K
$181.4K
How much do machine learning engineer jobs pay per year?
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 engineers make $300,000 a year?
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 15 days ago
Job description
Location: Remote (PST)
Duration: 10 Months
We are looking for an ML engineer with expertise in Unity Catalog and Feature Store in Databricks to help us build and maintain a solid foundation for our data and machine learning workflows. You will work on organizing data, managing access, and enabling machine learning models to operate efficiently in production
• Proficiency with Java
The ML Engineers will be supporting 3 web services applications - tech stack - Java 11 - Azure, AKS, and APIM.
• Set up and manage Unity Catalog in Databricks to organize and secure data access across teams
• Design and operationalize Feature Stores to support machine learning models in production
• Build efficient data pipelines to process and serve features to ML workflows
• Collaborate with teams using Databricks, Azure Cosmos DB, and other Azure tools to integrate data solutions
• Monitor and optimize the performance of pipelines and feature stores
• 5 - Strong experience with Unity Catalog in Databricks for managing data assets and access control
• 4 - Hands-on experience working with Databricks Feature Store or similar solutions
• 2 - Knowledge of building and maintaining scalable ETL pipelines in Databricks
• 2- Familiarity with Azure tools like Azure Cosmos DB and ACR
• 2- Understanding of machine learning workflows and how feature stores fit into the pipeline
• 5- Strong problem-solving skills and a collaborative mindset
• 3- Proficiency in Python and Spark for data engineering tasks
• 3- Experience with monitoring tools like Splunk or Datadog to ensure system reliability
• 2- Familiarity with AKS for deploying and managing containers
About Glow Networks
Sourced by ZipRecruiter
Industry
Telecommunications
Company size
51 - 200 Employees
Headquarters location
Dallas, TX, US
Year founded
2000