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Junior Machine Learning Engineer Jobs in Addison, TX

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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 ...

Confie

Machine Learning Engineer

Addison, TX · On-site +1

$110K - $130K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

... machine learning models and algorithms that will improve Confie's business outcome/customer experience Perform data cleansing, analysis, and feature engineering using Python Ability to work with ...

Quarterhill

Machine Learning Engineer

Frisco, TX · On-site

  • Medical

  • Dental

  • Retirement

  • PTO

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 ...

Yum

Machine Learning Engineer II

Plano, TX · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

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 ...

Yum Brands

Machine Learning Engineer II

Plano, TX · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

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 ...

Yum! Brands

Machine Learning Engineer II

Plano, TX

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

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

$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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All JobsMachine Learning Engineer JobsJunior Machine Learning Engineer JobsJunior Machine Learning Engineer Jobs in Addison, TX

Junior Machine Learning Engineer information

See Addison, TX salary details

$32.4K

$69.5K

$106K

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

As of Aug 18, 2026, the average yearly pay for junior machine learning engineer in Addison, TX is $69,506.00, according to ZipRecruiter salary data. Most workers in this role earn between $47,000.00 and $77,400.00 per year, depending on experience, location, and employer.

What does a junior machine learning engineer do?

As a junior machine learning engineer, you work in AI, performing research with algorithms and data modeling techniques. Machine learning involves using large collections of data to create systems that are capable of making predictions, and in this field, your duties and responsibilities revolve around using advanced mathematics to design applications for use in everything from stock trading to sports betting. Some machine learning efforts involve images, and this branch of the field is known as computer vision, while other techniques which focus on text are called natural language processing (NLP). Given these divisions, titles in machine learning include computer vision engineer, NLP scientist, or simply research scientist.

What kinds of projects and responsibilities can a junior machine learning engineer expect in their first year on the job?

As a Junior Machine Learning Engineer, you’ll typically work on tasks such as data preprocessing, building and testing simple models, and supporting more senior engineers in deploying machine learning solutions. Your responsibilities may also include cleaning datasets, implementing basic algorithms, and running experiments to evaluate model performance. You’ll often collaborate closely with data scientists, software engineers, and product teams to understand project goals and learn best practices. The role provides excellent opportunities to develop your technical skills, gain exposure to various stages of the ML pipeline, and gradually take on more complex projects as you grow.

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

To succeed as a Junior Machine Learning Engineer, you need a solid grasp of programming (especially Python), foundational knowledge of algorithms and statistics, and a relevant degree in computer science, mathematics, or a related field. Familiarity with machine learning frameworks such as TensorFlow or PyTorch and tools like scikit-learn, as well as experience with version control systems like Git, are typically required. Strong problem-solving abilities, attention to detail, and a willingness to learn from feedback are valuable soft skills that help you adapt and grow in the field. These skills ensure you can effectively develop, test, and improve machine learning models while collaborating with more experienced engineers and contributing to team projects.

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

AspectJunior Machine Learning EngineerData Scientist
Required CredentialsBachelor's in CS, Data Science, or related; some experience with ML frameworksBachelor's or higher in CS, Statistics, or related; often advanced certifications
Work EnvironmentDeveloping and deploying ML models, coding, testingData analysis, statistical modeling, interpreting data insights
Employer & Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, tech, consulting
Search & Comparison IntentYesYes

While both roles involve working with data and machine learning, Junior Machine Learning Engineers focus on building and deploying models, often with coding and engineering skills. Data Scientists analyze data, create statistical models, and interpret insights. The roles overlap but differ mainly in their core responsibilities and skill emphasis.

How much do junior machine learning engineers make?

Junior machine learning engineers typically earn between $70,000 and $100,000 annually, depending on location, education, and industry. Entry-level roles often require knowledge of programming languages like Python and familiarity with machine learning frameworks such as TensorFlow or PyTorch.
More about Junior Machine Learning Engineer jobs

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

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

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

Junior Machine Learning Engineer jobs near you
Infographic showing various Junior Machine Learning Engineer job openings in Addison, TX as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $69,506 per year, or $33.4 per hour.

Machine Learning Engineer

Rivago infotech inc

Dallas, TX • On-site

Other

Posted 4 days ago

Job description

Role: Machine Learning Engineer - Fraud Detection

Location: Dallas, TX (100% Onsite)

 

Role Summary

We are looking for a Machine Learning Engineer to build and support production-grade fraud detection solutions. The role focuses on real-time inference, feature engineering, APIs, graph-based fraud detection, and production deployment support.

 

Key Skills

  • Machine Learning Engineering and Real-Time Inference
  • Python, APIs, and Microservices
  • Google Cloud Platform and Databricks
  • Neo4j / Graph Databases and Feature Stores
  • Data Pipelines and Feature Engineering
  • MLOps, Monitoring, and Production Support
  • Agentic AI Architecture (good to have)

 

Responsibilities

  • Build and deploy fraud detection services for production use.
  • Develop low-latency inference solutions with a target of less than 250 ms.
  • Design feature engineering pipelines for ML use cases.
  • Integrate ML models with REST APIs and microservices.
  • Support graph-based fraud detection using Neo4j.
  • Improve scoring performance, reliability, and scalability.
  • Work with MLOps teams for releases, monitoring, and production support.
  • Support data quality, governance, and operational activities.

 

Required Qualifications

  • Hands-on experience in Python and ML model deployment.
  • Experience with APIs, microservices, and production ML systems.
  • Knowledge of data pipelines, data engineering, and feature stores.
  • Exposure to Google Cloud Platform, Databricks, Data Lake, or Data Warehouse platforms.
  • Basic understanding of MLOps, monitoring, and release support.
  • Good communication and problem-solving skills.

 

Nice to Have

  • Fraud detection, risk analytics, or scoring model experience.
  • Experience with Neo4j or graph-based ML solutions.
  • Understanding of Agentic AI architecture.

Apply