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Senior Machine Learning Engineer Jobs in Frisco, TX

UNAVAILABLE

Machine Learning Engineer

Frisco, TX · On-site

$140 - $190/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 ...

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

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 - $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 ...

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 ...

Capital One Group

Lead Machine Learning Engineer

Plano, TX · On-site

$179 - $205/hr

R249230Lead Machine Learning Engineer**Join the Dealer Tech division within Capital One's Financial Services Technology group, where we develop and support cutting edge technological solutions that ...

Capital One

Lead Machine Learning Engineer

Plano, TX · On-site

$98K - $129K/yr

Lead Machine Learning Engineer Join the Dealer Tech division within Capital One's Financial Services Technology group, where we develop and support cutting edge technological solutions that ...

Capital One

Lead Machine Learning Engineer

Plano, TX · On-site

$98K - $129K/yr

Lead Machine Learning Engineer Join the Dealer Tech division within Capital One's Financial Services Technology group, where we develop and support cutting edge technological solutions that ...

Capital One

Lead Machine Learning Engineer

Plano, TX · On-site

$98K - $130K/yr

Lead Machine Learning Engineer Join the Dealer Tech division within Capital One's Financial Services Technology group, where we develop and support cutting edge technological solutions that ...

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Showing results 21-40

All JobsMachine Learning Engineer JobsSenior Machine Learning Engineer JobsSenior Machine Learning Engineer Jobs in Frisco, TX

Senior Machine Learning Engineer information

See Frisco, TX salary details

$56.1K

$119.3K

$172.9K

How much do senior machine learning engineer jobs pay per year?

As of Sep 5, 2026, the average yearly pay for senior machine learning engineer in Frisco, TX is $119,274.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $135,200.00 per year, depending on experience, location, and employer.

What does a senior machine learning engineer do?

A Senior Machine Learning Engineer designs, develops, and implements machine learning models to solve complex problems. They are responsible for selecting appropriate algorithms, preprocessing data, and optimizing model performance. Additionally, they collaborate with data scientists, software engineers, and product teams to integrate machine learning solutions into production systems. Senior engineers also mentor junior team members and contribute to setting technical direction for machine learning projects.

What are some common challenges senior machine learning engineers face when deploying models to production, and how can they be addressed?

Senior Machine Learning Engineers often encounter challenges related to model scalability, maintaining performance in real-world scenarios, and ensuring reliable integration with existing systems. Addressing these challenges typically involves thorough testing, implementing robust monitoring for model drift, and collaborating closely with DevOps and software engineering teams to streamline deployment pipelines. Staying updated on best practices in MLOps and adopting tools for automated deployment and monitoring can greatly improve the reliability and efficiency of production models.

What are the key skills and qualifications needed to thrive as a senior machine learning engineer, and why are they important?

To thrive as a Senior Machine Learning Engineer, you need advanced knowledge of machine learning algorithms, statistical modeling, and programming languages like Python or Java, typically supported by a degree in computer science or a related field. Experience with frameworks and tools such as TensorFlow, PyTorch, scikit-learn, and cloud platforms, as well as familiarity with version control and CI/CD systems, is essential. Strong problem-solving, communication, and leadership skills help you collaborate effectively and mentor junior team members. These capabilities are crucial for designing scalable ML solutions and driving impactful results within complex, dynamic projects.

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

AspectSenior Machine Learning EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, ML, or related; experience with ML frameworksBachelor's/Master's in CS, Statistics, or related; strong analytical skills
Work EnvironmentDevelops and deploys ML models in production systemsAnalyzes data, builds models, and provides insights
Industry UsageTech, finance, healthcare, e-commerceResearch, finance, marketing, tech

While both roles require strong technical skills and knowledge of machine learning, Senior Machine Learning Engineers focus more on deploying scalable ML solutions in production environments, whereas Data Scientists primarily analyze data and develop models for insights. The roles often overlap but differ in their core responsibilities and focus areas.

What are the most commonly searched types of Machine Learning Engineer jobs in Frisco, TX?

The most popular types of Machine Learning Engineer jobs in Frisco, TX are:

What are popular job titles related to Senior Machine Learning Engineer jobs in Frisco, TX?

For Senior Machine Learning Engineer jobs in Frisco, TX, the most frequently searched job titles are:

What job categories do people searching Senior Machine Learning Engineer jobs in Frisco, TX look for?

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

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

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

Senior Machine Learning Engineer jobs near you
Infographic showing various Senior Machine Learning Engineer job openings in Frisco, TX as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 25% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $119,274 per year, or $57.3 per hour.

Machine Learning Engineer

UNAVAILABLE

Frisco, TX • On-site

$140 - $190/hr

Other

Re-posted yesterday

Job description

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, develop, and deploy state-of-the-art computer vision and language models that power scalable, real-world solutions. You’ll work with large-scale image and video data, building and optimizing production-grade vision systems while contributing clean and modular code to shared repositories.

As part of our AI team, you’ll collaborate closely with engineering teams to deliver high-impact features for our growing SaaS platform. The ideal candidate brings hands‑on experience deploying computer vision and language models in production and applying MLOps best practices on cloud platforms.

Responsibilities
  • Fine‑tune and deploy computer vision and deep learning models for object detection, object tracking, and OCR at scale.
  • Develop vision‑language models and Mixture of Experts architectures, from experimental design through production deployment.
  • Architect Retrieval‑Augmented Generation (RAG) systems, including vector store design, hybrid search strategies, chunking pipelines, and context relevance evaluation.
  • Apply MLOps best practices for training, evaluation, deployment, and monitoring of production grade computer vision models, with an emphasis on clean, modular, maintainable code.
  • Contribute to our machine learning repositories and optimize models for performance, scalability, and real‑time inference across edge and cloud environments.
  • Drive performance optimization and scalability of ML systems across edge and cloud environments.
  • Collaborate with cross‑functional teams to integrate computer vision solutions into end‑to‑end products, translating research outcomes into measurable platform impact.

This list of responsibilities might not cover everything you'll end up doing.

Qualifications
  • 5+ years of hands‑on machine learning experience, with deep specialization in computer vision and a proven track record of shipping models to production.
  • Master's degree required (Ph.D. preferred) in Computer Science, Machine Learning, or a closely related field.
  • Extensive knowledge of computer vision architectures such as Vision Transformers and VLMs along with OpenCV and PIL.
  • Experience with MLOps tools (MLflow, Kubeflow, Docker, Kubernetes) able to own the full model lifecycle from experimentation through production monitoring.
  • Experience building and deploying LLM-based systems and Retrieval‑Augmented Generation (RAG) pipelines, including vector store integration and retrieval evaluation.
  • Strong communicator who can translate complex research findings into actionable decisions for engineering and product stakeholders.
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