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Machine Learning Engineer Jobs in The Colony, TX

Photon

Machine Learning Engineer - NJ

Addison, TX · On-site

$54 - $71.50/hr

We are seeking a Machine Learning Engineer to design and develop robust analytics models using statistical and machine learning algorithms. In this role, you will work closely with product and ...

Photon

Machine Learning Engineer - NJ

Addison, TX · On-site

$54 - $71.50/hr

We are seeking a Machine Learning Engineer to design and develop robust analytics models using statistical and machine learning algorithms. In this role, you will work closely with product and ...

Vanguard

Manager, Machine Learning Engineer

Dallas, TX · On-site

$101K - $133K/yr

Leads a team of Machine Learning Engineers responsible for designing, building, deploying, and scaling AI/ML solutions that support Financial Advisory Services (FAS) business objectives. Partners ...

Equinix

AI/Machine Learning Engineer

Dallas, TX · Remote

... ML engineering, or related roles, with demonstrated experience in building and integrating production-grade systems * Bachelor's degree in Computer Science, Machine Learning, Data Science, or a ...

Equinix, Inc.

AI/Machine Learning Engineer

Dallas, TX · On-site

... ML engineering, or related roles, with demonstrated experience in building and integrating production-grade systems * Bachelor's degree in Computer Science, Machine Learning, Data Science, or a ...

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Showing results 1-20

All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in The Colony, TX

Machine Learning Engineer information

See The Colony, TX salary details

$29.2K

$119.4K

$179.4K

How much do machine learning engineer jobs pay per year?

As of Jul 15, 2026, the average yearly pay for machine learning engineer in The Colony, TX is $119,408.00, according to ZipRecruiter salary data. Most workers in this role earn between $94,100.00 and $143,700.00 per year, depending on experience, location, and employer.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-demand industries or companies can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially in tech giants or startups with significant funding.

What do machine learning engineers do?

Machine learning engineers develop algorithms and models that enable computers to learn from data and make predictions or decisions. They often work with large datasets, use programming languages like Python or Java, and utilize tools such as TensorFlow or PyTorch to build, test, and deploy machine learning systems in production environments.

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

What are the key skills and qualifications needed to thrive as a Machine Learning Engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as AI advances, as they develop and refine algorithms, models, and systems. Roles that require complex problem-solving, creativity, and domain expertise—such as healthcare professionals, data scientists, software developers, cybersecurity specialists, and AI ethics officers—are also expected to persist due to their reliance on human judgment and specialized knowledge. These jobs often involve skills that are difficult for AI to fully replicate or replace.

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?

Senior machine learning engineers and data scientists with extensive experience, advanced skills in deep learning, and proficiency with tools like TensorFlow or PyTorch can earn $300,000 or more annually, especially in high-cost-of-living areas or top tech companies. Compensation often includes base salary, bonuses, and stock options, reflecting their expertise and impact on business outcomes.

What are some common challenges faced by Machine Learning Engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

What is the difference between Machine Learning Engineer vs Data Scientist?

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, 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.

More about Machine Learning Engineer jobs
What are the most commonly searched types of Machine Learning Engineer jobs in The Colony, TX? The most popular types of Machine Learning Engineer jobs in The Colony, TX are:
What are popular job titles related to Machine Learning Engineer jobs in The Colony, TX? For Machine Learning Engineer jobs in The Colony, TX, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer jobs in The Colony, TX look for? The top searched job categories for Machine Learning Engineer jobs in The Colony, TX are:
What cities near The Colony, TX are hiring for Machine Learning Engineer jobs? Cities near The Colony, TX with the most Machine Learning Engineer job openings:
Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in The Colony, TX as of July 2026, with employment types broken down into 91% Full Time, 7% Part Time, and 2% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $119,408 per year, or $57.4 per hour.
Machine Learning Engineer, Unity Catalog

Machine Learning Engineer, Unity Catalog

Glow Networks

Dallas, TX • On-site

Full-time

Re-posted 26 days ago

Job description

Job Description: Machine Learning Engineer, Unity Catalog
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

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