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Machine Learning Testing Jobs in Texas (NOW HIRING)

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

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

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

... and testing workflows. 4+ years of related experience building high throughput scalable applications or building machine learning models.Proficiency in one or more object-oriented programming ...

SUMMARY The Machine Learning Engineer provides hands-on expertise in designing, implementing, and ... testing and validation EXPERIENCE AND KNOWLEDGE • Bachelor's degree in related field and 5-8 ...

SUMMARY The Machine Learning Engineer provides hands-on expertise in designing, implementing, and ... testing and validation EXPERIENCE AND KNOWLEDGE Bachelor's degree in related field and 5-8 years ...

This includes idea generation, architecture, design, development, and testing of products ... We are currently looking for a Director of Machine Learning who will take the lead and manage ...

This includes idea generation, architecture, design, development, and testing of products ... We are currently looking for a Director of Machine Learning who will take the lead and manage ...

This includes idea generation, architecture, design, development, and testing of products ... We are currently looking for a Director of Machine Learning who will take the lead and manage ...

... and testing workflows.","responsibilities":"Collaborate with other MLEs to build scalable ... Experience building data processing pipelines and large scale machine learning systems with ...

... and testing workflows.","responsibilities":"Collaborate with other MLEs to build scalable ... Experience building data processing pipelines and large scale machine learning systems with ...

... and testing workflows.","responsibilities":"Collaborate with other MLEs to build scalable ... Experience building data processing pipelines and large scale machine learning systems with ...

Senior Machine Learning Engineer

Austin, TX · On-site

$121.40K - $160.10K/yr

... testing. You will also work on building out a SOTA machine learning platform. We're looking for strong engineers well versed with modern large scale machine learning platforms with a solid grasp of ...

Senior Machine Learning Engineer

Plano, TX · On-site

$100K - $137.30K/yr

Senior Machine Learning Engineer Location: Ann Arbor, Michigan Experience Level: 7+ Years ... Solid understanding of statistical analysis , probability, hypothesis testing, and experimental ...

Senior Machine Learning Engineer

Plano, TX · On-site

$100K - $137.30K/yr

We are looking for an experienced Senior Machine Learning Engineer with deep expertise in ... Solid understanding of statistical analysis , probability, hypothesis testing, and experimental ...

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Machine Learning Testing information

See Texas salary details

$12

$21

$28

How much do machine learning testing jobs pay per hour?

As of May 30, 2026, the average hourly pay for machine learning testing in Texas is $21.26, according to ZipRecruiter salary data. Most workers in this role earn between $18.37 and $23.75 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.
What are the most commonly searched types of Machine Learning Testing jobs in Texas? The most popular types of Machine Learning Testing jobs in Texas are:
Infographic showing various Machine Learning Testing job openings in Texas as of May 2026, with employment types broken down into 3% As Needed, 82% Full Time, 10% Part Time, 3% Contract, and 2% Nights. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $44,224 per year, or $21.3 per hour.

Machine Learning Engineer

Avride

Austin, TX • On-site

Full-time

Posted 5 days ago


Job description

About the Team
Avride develops autonomous vehicle and delivery robot technology, leveraging deep expertise in autonomous systems. With the recent launch of our robotaxi service in Dallas, we are accelerating innovation and redefining the future of mobility.
Our team builds self-driving solutions from the ground up, with machine learning at the core of our development pipeline to enable safe and intelligent navigation. We design and deploy state-of-the-art models to address key challenges in autonomous systems, utilizing advanced deep learning architectures such as Convolutional Neural Networks (CNNs), Transformers, and Multimodal Large Language Models (MLLMs). These models power both onboard and offboard applications, ensuring robust and efficient operation. Your work will directly contribute to enhancing the performance, safety, and reliability of Avride's autonomous vehicles and delivery robots.
About the Role
We are looking for an experienced Machine Learning Engineer with a strong background in developing and deploying modern machine learning solutions for complex real-world challenges. In this role, you will conduct experiments, manage large-scale datasets, and implement deep learning models tailored for autonomous systems.
You will utilize cloud platforms, orchestration tools, and machine learning frameworks to develop scalable and efficient solutions. Additionally, you will analyze the latest research, assess the applicability of emerging deep learning techniques, and drive innovation in autonomous vehicle technology.
What You'll Do
  • Develop and Optimize Machine Learning Models: Design, implement, and refine deep learning models to ensure efficiency, scalability, and robustness. This may include developing models for understanding a self-driving vehicle's surroundings or predicting the intentions of other road users.
  • Curate and Manage Large-Scale Datasets: Oversee data collection, preprocessing, and augmentation to maintain high-quality datasets for training and evaluation.
  • Enhance and Maintain Training Pipelines: Develop efficient workflows for training, validation, and testing, incorporating distributed training, hyperparameter tuning, and automated monitoring.
  • Improve Model Deployment and Efficiency: Optimize inference performance, model compression, and deployment across various hardware platforms.
  • Explore and Apply Cutting-Edge ML Techniques: Stay up to date with advancements in deep learning and experiment with novel approaches to improve model performance.
  • Collaborate with Cross-Functional Teams: Work closely with researchers, software engineers, and robotics experts to integrate machine learning solutions into real-world autonomous systems.
What You'll Need
  • Strong understanding of fundamental machine learning algorithms and neural network techniques.
  • Expertise in at least one modern machine learning domain, such as computer vision, large language models, or generative AI.
  • At least three years of experience developing neural network-based algorithms, including data collection, training, and deployment.
  • Proficiency in Python and ML frameworks such as PyTorch, TensorFlow, or JAX, along with PySpark, NumPy, and SciPy.
  • Working knowledge of C++ and SQL.
  • Ability to quickly absorb new concepts by reviewing research papers, technical reports, and documentation.
  • Strong collaboration and communication skills, with the ability to align technical work with business objectives and drive results.
Nice to Have
  • Advanced degree in Computer Science, Machine Learning, Robotics, or a related field.
  • Experience developing ML algorithms for autonomous vehicles or robotics applications.
  • Familiarity with neural network deployment and optimization tools such as triton, TensorRT, or similar frameworks.
  • Proven ability to set and achieve mid- and long-term goals, prioritize tasks, and meet deadlines independently.
  • Experience working in cross-functional teams within a multidisciplinary environment.
  • Publications in top-tier ML conferences or contributions to patent applications or ML-related open-source projects.

Candidates are required to be authorized to work in the U.S. The employer is not offering relocation sponsorship, and remote work options are not available.
Avride is an equal opportunity employer and committed to providing reasonable accommodations to qualified applicants and employees with disabilities to ensure they have equal access to employment opportunities. Avride complies with the Americans with Disabilities Act (ADA), if you need a reasonable accommodation to assist with the application or hiring process, or to perform the essential functions of a job, please email jobs@avride.ai.