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Machine Learning Engineer Jobs in Richardson, TX

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Machine Learning Engineer

Frisco, TX · On-site

$150 - $200/hr

Overview Quarterhill is seeking a Machine Learning Engineer to join our forward-thinking team building the next generation of Intelligent Transportation Systems . In this role, you will design ...

Quarterhill

Machine Learning Engineer

Frisco, TX · On-site

Overview Quarterhill is seeking a Machine Learning Engineer to join our forward-thinking team building the next generation of Intelligent Transportation Systems . In this role, you will design ...

SuperMom's LLC

Machine Learning Engineer II

Irving, TX · On-site

$150 - $200/hr

As a Machine Learning Engineer II at 7-Eleven, you will collaborate with cross-functional teams and work closely with senior architects to implement scalable and efficient data solutions. Your ...

7-ELEVEN

Machine Learning Engineer II

Irving, TX · On-site

As a Machine Learning Engineer II at 7-Eleven, you will collaborate with cross-functional teams and work closely with senior architects to implement scalable and efficient data solutions. Your ...

7-Eleven

Machine Learning Engineer II

Irving, TX · On-site

As a Machine Learning Engineer II at 7-Eleven, you will collaborate with cross-functional teams and work closely with senior architects to implement scalable and efficient data solutions. Your ...

Capital One

Lead Machine Learning Engineer

Plano, TX · On-site

$98K - $129K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

Capital One

Lead Machine Learning Engineer

Plano, TX

$98K - $130K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

Yum! Brands

Machine Learning Engineer II

Plano, TX · On-site

As a Machine Learning Engineer, you will play a crucial role in developing and deploying cutting-edge machine learning models and solutions to enhance various aspects of our business operations, from ...

Capital One

Lead Machine Learning Engineer

Plano, TX · On-site +1

$98K - $129K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

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All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Richardson, TX

Machine Learning Engineer information

See Richardson, TX salary details

$28.6K

$116.9K

$175.7K

How much do machine learning engineer jobs pay per year?

As of Sep 9, 2026, the average yearly pay for machine learning engineer in Richardson, TX is $116,939.00, according to ZipRecruiter salary data. Most workers in this role earn between $92,200.00 and $140,800.00 per year, depending on experience, location, and employer.

What is a machine learning engineer?

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 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 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.

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

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The top searched job categories for Machine Learning Engineer jobs in Richardson, TX are:

What cities near Richardson, TX are hiring for Machine Learning Engineer jobs?

Cities near Richardson, TX with the most Machine Learning Engineer job openings:

Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Richardson, TX as of August 2026, with employment types broken down into 1% As Needed, 76% Full Time, 22% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $116,939 per year, or $56.2 per hour.

Machine Learning Engineer

Plano, TX • On-site

Smart Info Solutions llc
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Job description

Job Title: Machine Learning Engineer
Location: Plano, TX – Onsite/Hybrid
Job Type: Contract
Work Authorization: STRICTLY ON W2

Job Summary

We are looking for a Machine Learning Engineer with a strong engineering and model-development mindset. The ideal candidate will have hands-on experience with Python, machine learning model development, deployment, troubleshooting, and production support across Windows and Linux environments.

This is not primarily a DevOps or SRE position. We are looking for someone who understands the engineering side of machine learning, including model development and lifecycle, while also being comfortable supporting ML applications in production.

Key Responsibilities

  • Develop, maintain, deploy, and troubleshoot machine learning applications and models.

  • Work closely with Data Scientists and ML Engineers to take models from development through production.

  • Develop and maintain Python-based ML applications and services.

  • Support ML applications running on Windows and Linux environments.

  • Manage and troubleshoot Kubernetes clusters and Docker containers supporting ML workloads.

  • Deploy and manage machine learning models throughout their lifecycle.

  • Debug complex production issues using Python, logs, monitoring, and troubleshooting tools.

  • Implement monitoring and alerting using Datadog to ensure application and model health.

  • Automate repetitive engineering and operational tasks using Python and other scripting technologies.

  • Work with CI/CD pipelines to support reliable ML application and model deployments.

  • Collaborate with engineering, data science, and infrastructure teams.

  • Ensure ML applications meet requirements for performance, security, scalability, and availability.

  • Document architecture, deployment processes, model workflows, and troubleshooting procedures.

Required Skills

  • Strong hands-on Python programming experience.

  • Strong understanding of Machine Learning concepts and workflows.

  • Experience with ML model development and/or model engineering.

  • Hands-on experience with ML model deployment and lifecycle management.

  • Experience supporting applications in both Windows and Linux environments.

  • Experience with on-premises servers and production environments.

  • Hands-on experience with Kubernetes and Docker.

  • Experience troubleshooting distributed applications and production issues.

  • Experience with Datadog or similar monitoring/observability tools.

  • Experience with CI/CD pipelines for ML applications.

  • Familiarity with AWS cloud services.

  • Understanding of DevOps/SRE practices as they relate to supporting ML applications.

  • Strong problem-solving and debugging skills.

  • Excellent communication and collaboration skills.

Ideal Candidate Profile

We are specifically looking for an engineering-oriented Machine Learning Engineer who can understand and contribute to model development, not just infrastructure or operations.

Strong candidates will have:

  • Machine Learning + Python development experience

  • ML model development/deployment experience

  • Production application troubleshooting experience

  • Kubernetes/Docker experience

  • Windows/Linux administration experience

  • Experience working closely with Data Scientists

The candidate should be stronger on ML engineering and application/model development than pure infrastructure or operations.

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