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Machine Learning Testing Jobs (NOW HIRING)

ExtendMyTeam

Machine Learning Engineer

Austin, TX · On-site

Support experimentation, evaluation, testing, and continuous improvement of AI systems * Stay current with emerging AI, LLM, and machine learning technologies Required Experience / Ideal Background ...

Avride

Machine Learning Engineer

Austin, TX

Develop efficient workflows for training, validation, and testing, incorporating distributed ... Strong understanding of fundamental machine learning algorithms and neural network techniques.

CoVar

Machine Learning Engineer

Durham, NC

CI/CD pipelines and regression testing. * AI/ML expertise: Machine learning fundamentals; Deep knowledge of state-of-the-art in any of the following: computer vision (preferred), natural language ...

Avride

Machine Learning Engineer

Austin, TX · On-site

They are seeking an experienced Machine Learning Engineer to design, implement, and optimize ... Develop efficient workflows for training, validation, and testing, incorporating distributed ...

Micron

Machine Learning Engineer

Boise, ID

Position requires experience in: 1. Building and executing end-to-end ML systems automating training, testing, and deploying Machine Learning models in cloud platforms 2. Machine learning frameworks ...

Hive

Machine Learning Manager

Seattle, WA · On-site

$180K - $250K/yr

Machine Learning Manager In order to execute our vision, we're constantly growing our machine ... testing, and deployment in production. * Drive delivery for our product milestones, continually ...

Machina Labs

Machine Learning Engineer

Chatsworth, CA · On-site

$160K - $190K/yr

Strong experience designing, building, training, and testing machine learning models end-to-end. * Proven ability to work with raw, unstructured, or incomplete data, including data collection ...

Spotify

Machine Learning Engineer

... testing, evaluation, etc., both inside the team as well as throughout the organization. Qualifications : Required : • Strong background in machine learning • Expertise in statistics and ...

Sarian, Inc.

Python Developer

Pittsburgh, PA · On-site

$48.75 - $67.25/hr

Data Analysis/Machine Learning. * Testing/Debugging/Security. * Writing, testing, and debugging Python code for various applications. * Developing server-side logic, back-end components, and APIs.

Spotify

Machine Learning Engineer

... testing, evaluation, etc., both inside the team as well as throughout the organization. Qualifications : Required : • You have a strong background in machine learning, enjoy applying theory to ...

Micron Technology

Machine Learning Engineer

Boise, ID · On-site

Position requires experience in: 1. Building and executing end-to-end ML systems automating training, testing, and deploying Machine Learning models in cloud platforms 2. Machine learning frameworks ...

Motorola

Machine Learning Engineer

Los Angeles, CA

Contribute to the design of data pipelines and infrastructure for training, testing, and validating ... Stay current with the latest Machine Learning research for wireless and embedded systems. * Perform ...

AI Squared

Machine Learning Engineer

Washington, DC

Machine Learning Engineer Washington, DC (Hybrid) About the Role: We are seeking a highly skilled ... Develop CI/CD pipelines for ML workflows, integrating testing, validation, and automated deployment.

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How much do machine learning testing jobs pay per hour?

As of Jun 3, 2026, the average hourly pay for machine learning testing in the United States is $22.82, according to ZipRecruiter salary data. Most workers in this role earn between $19.71 and $25.48 per hour, depending on experience, location, and employer.

What is a Machine Learning Testing job?

A Machine Learning Testing job involves evaluating and validating machine learning models to ensure they function correctly, efficiently, and ethically. This includes testing for accuracy, reliability, bias, and performance under different conditions. Professionals in this role employ techniques such as unit testing, integration testing, data validation, and model performance monitoring. They also work closely with data scientists and engineers to debug issues and improve model robustness. The goal is to ensure that machine learning systems perform as expected and meet business or regulatory requirements.

What are the key skills and qualifications needed to thrive in the Machine Learning Testing position, and why are they important?

To excel in Machine Learning Testing, you need a solid understanding of machine learning concepts, data analysis, and programming skills in languages like Python, as well as a background in quality assurance or software testing. Familiarity with frameworks such as TensorFlow, PyTorch, automated testing tools, and relevant certifications like ISTQB are highly beneficial. Strong attention to detail, analytical thinking, and effective communication skills help testers identify issues and collaborate with data scientists and developers. These competencies are essential to ensure the reliability, fairness, and accuracy of machine learning models deployed in production environments.

What are the typical challenges faced by professionals in Machine Learning Testing roles?

Professionals in Machine Learning Testing often encounter challenges such as dealing with non-deterministic model outputs, insufficient or imbalanced datasets, and unclear or evolving testing criteria. They may need to work closely with data scientists and engineers to develop robust test cases and validation methods tailored for dynamic machine learning systems. Staying updated on advancements in testing methodologies and tools is also important, as the field evolves rapidly. Successfully overcoming these challenges leads to higher quality models and more reliable AI solutions for end users.
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Machine Learning Testing jobs near you
Infographic showing various Machine Learning Testing job openings in the United States as of May 2026, with employment types broken down into 3% As Needed, 66% Full Time, 24% Part Time, and 7% Contract. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $47,468 per year, or $22.8 per hour.

Machine Learning Engineer

ExtendMyTeam

Austin, TX • On-site

Full-time

Posted 15 days ago

Job description

Join a high-growth financial technology organization focused on delivering modern digital banking and software solutions to financial institutions and enterprise clients. This team is investing heavily in AI-driven innovation to improve operational efficiency, accelerate software delivery, and streamline implementation processes across a large-scale delivery organization.

This is an opportunity to work on highly visible initiatives focused on automation, workflow optimization, and practical AI applications that directly impact customer delivery and operational performance.

Position Summary

We are seeking a Machine Learning Engineer to help design, implement, and scale AI-enabled solutions that improve software delivery workflows, automate operational processes, and enhance implementation efficiency. This individual will partner closely with engineering, implementation, product, and delivery teams to identify process bottlenecks and build practical AI-driven solutions that improve execution and scalability.

This is a hands-on engineering role focused on production systems, workflow automation, and AI implementation rather than purely research-oriented machine learning work.

Responsibilities

  • Design and develop AI/ML-enabled applications and workflow automation solutions

  • Build scalable machine learning pipelines and production-ready systems

  • Collaborate cross-functionally with engineering, implementation, product, and delivery teams

  • Identify operational inefficiencies and develop automation solutions to improve processes and delivery cycles

  • Integrate AI and machine learning solutions into production environments

  • Support experimentation, evaluation, testing, and continuous improvement of AI systems

  • Stay current with emerging AI, LLM, and machine learning technologies

Required Experience / Ideal Background

  • 5–8 years of relevant software engineering and/or machine learning experience

  • Strong Python engineering background

  • Experience working with AI/LLM technologies and frameworks such as OpenAI, Claude, PyTorch, TensorFlow, LangChain, or similar tools

  • Experience building and deploying production-grade applications, automation systems, or ML solutions

  • Familiarity with cloud platforms and scalable infrastructure environments

  • Experience within SaaS, enterprise software, fintech, or implementation-heavy technology organizations preferred

  • Strong problem-solving, communication, and collaboration skills

  • Experience working cross-functionally with technical and operational teams

Additional Information

  • Hybrid opportunity located in Austin, TX

  • Applicants must be authorized to work in the U.S. without sponsorship

  • Competitive compensation, benefits, flexible time off, and career development opportunities