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Machine Learning Engineer Jobs in Austin, TX (NOW HIRING)

ExtendMyTeam

Machine Learning Engineer

Austin, TX · On-site

As a Machine Learning Engineer, you will help build and operate production systems that power fraud detection and risk-related products. You'll work closely with data scientists and engineers to ...

1872 Consulting

Machine Learning Engineer

Austin, TX · On-site

Machine Learning Engineer (Austin, TX) Striveworks is a leader in Machine Learning Operations for highly regulated industries such as the Department of Defense/U.S. Military. They enable their ...

Avride

Machine Learning Engineer

Austin, TX · On-site +1

Machine Learning Engineer Austin, TX About the Team Avride develops autonomous vehicle and delivery robot technology, leveraging deep expertise in autonomous systems. With the recent launch of our ...

ExtendMyTeam

Machine Learning Engineer

Austin, TX

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 ...

PayPal

Machine Learning Engineer

Austin, TX · On-site

Machine Learning Engineer This job will validate and develop machine learning models and algorithms to solve complex problems. You will work closely with senior engineers, data scientists, and ...

Q2

Machine Learning Engineer

Austin, TX · On-site

Machine Learning Engineer Q2 is a leading provider of digital banking and lending solutions to banks, credit unions, alternative finance companies, and fintechs in the U.S. and internationally. Our ...

Apple

Machine Learning Engineer

Austin, TX · On-site

Machine Learning Engineer Imagine what you could do here! The people here at Apple don't just create products -- they build the kind of wonder that's revolutionized entire industries. It's the ...

Apple

Machine Learning Engineer

Austin, TX · On-site

We are looking for a passionate, highly motivated, and hands-on applied Machine Learning Engineer. This role will assist our Online Retail Decision Automation team by helping to research and develop ...

Avride

Machine Learning Engineer

Austin, TX

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 ...

Q2

Machine Learning Engineer

Austin, TX

SUMMARY The Machine Learning Engineer provides hands-on expertise in designing, implementing, and scaling AI solutions, while collaborating with cross-functional teams to advance machine learning ...

Avride

Machine Learning Engineer

Austin, TX · On-site

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 ...

Q2 Software, Inc.

Machine Learning Engineer

Austin, TX · On-site

SUMMARY The Machine Learning Engineer provides hands-on expertise in designing, implementing, and scaling AI solutions, while collaborating with cross-functional teams to advance machine learning ...

Shipwell

Machine Learning Engineer

Austin, TX · On-site +1

About the Role As a Machine Learning Engineer at Shipwell, you'll play a pivotal role in building and scaling our AI-powered logistics solutions. You'll design, develop, and maintain the data ...

Q2 Software, Inc.

Machine Learning Engineer

Austin, TX · On-site

SUMMARY The Machine Learning Engineer provides hands-on expertise in designing, implementing, and scaling AI solutions, while collaborating with cross-functional teams to advance machine learning ...

Apple

Machine Learning Engineer

Austin, TX · On-site

$132.10K - $244.60K/yr

We are looking for a passionate, highly motivated, and hands-on applied Machine Learning Engineer. This role will assist our Online Retail Decision Automation team by helping to research and develop ...

Apple

Machine Learning Engineer

Austin, TX · On-site

$132.10K - $244.60K/yr

We are looking for a passionate, highly motivated, and hands-on applied Machine Learning Engineer. This role will assist our Online Retail Decision Automation team by helping to research and develop ...

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Machine Learning Engineer information

See Austin, TX salary details

$31.2K

$127.6K

$191.8K

How much do machine learning engineer jobs pay per year?

As of May 28, 2026, the average yearly pay for machine learning engineer in Austin, TX is $127,637.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,600.00 and $153,600.00 per year, depending on experience, location, and employer.

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 are Machine Learning Engineers?

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 jobs make $3,000 a month without a degree?

A Machine Learning Engineer typically requires a degree, but roles such as data annotator, technical support specialist, or freelance programmer can sometimes earn around $3,000 monthly without a formal degree, especially with relevant skills and experience. These jobs often involve self-taught skills, online certifications, or on-the-job training and may require proficiency in tools like Python or cloud platforms.

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
What are the most commonly searched types of Machine Learning Engineer jobs in Austin, TX? The most popular types of Machine Learning Engineer jobs in Austin, TX are:
What are popular job titles related to Machine Learning Engineer jobs in Austin, TX? For Machine Learning Engineer jobs in Austin, TX, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer jobs in Austin, TX look for? The top searched job categories for Machine Learning Engineer jobs in Austin, TX are:
What cities near Austin, TX are hiring for Machine Learning Engineer jobs? Cities near Austin, TX with the most Machine Learning Engineer job openings:
Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Austin, TX as of May 2026, with employment types broken down into 100% Full Time. Highlights an 71% In-person, and 29% Remote job distribution, with an average salary of $127,637 per year, or $61.4 per hour.

Machine Learning Engineer

ExtendMyTeam

Austin, TX • On-site

Other

This job post has expired 1 day ago. Applications are no longer accepted.

Job description

The Risk & Fraud team helps customers take a proactive stance against fraud while managing the risks inherent to their business. We build and enhance products that evolve with the ever-changing fraud landscape, delivering tangible value to customers. Our solutions allow financial institutions to focus more of their time and energy on serving their customers and communities.

As a Machine Learning Engineer, you will help build and operate production systems that power fraud detection and risk-related products. You’ll work closely with data scientists and engineers to bring models into production, ensuring they are reliable, scalable, and maintainable.

You’ll gain hands-on experience working across model development, evaluation, deployment, monitoring, and ongoing improvements. This is an applied engineering role — the software you build will solve real-world problems and must be production-ready, reliable, and testable.

A Typical Day

Your Key Responsibilities

  • Build and maintain systems and pipelines that support training, evaluation, and inference for machine learning models

  • Contribute to deploying machine learning models into production environments and ensuring they run reliably at scale

  • Write clean, maintainable, and well-tested code following production engineering best practices

  • Support monitoring and troubleshooting production ML systems, including data pipelines and model performance

  • Collaborate with data scientists and engineers to productionalize models and integrate them into scalable applications

  • Help improve the reliability, scalability, and performance of ML systems over time

  • Contribute to improving tooling and infrastructure that supports the ML development lifecycle

You Are More Likely to Excel If You:

  • Enjoy autonomy in your work and take ownership of team goals while balancing speed with long-term impact

  • Have empathy for end users and measure success through both customer value and technical quality

  • Are enthusiastic about machine learning, engineering excellence, and continuous professional development

Bring Your Passion, Do What You Love. Here’s What We’re Looking For

Must-Haves

  • Bachelor’s degree in a relevant field with 2+ years of related experience, or equivalent practical experience

  • Proficiency in Python

  • Experience writing clean, maintainable code and using version control tools such as Git

  • Experience with machine learning frameworks such as PyTorch, TensorFlow, or scikit-learn

Nice to Have

  • Experience building end-to-end ML systems, including data pipelines, model training, deployment, and monitoring

  • Experience deploying or integrating machine learning models into applications

  • Experience building APIs, backend services, or working with distributed systems

  • Familiarity with cloud platforms such as AWS, GCP, or Azure

  • Exposure to MLOps concepts such as CI/CD and model monitoring

  • Experience working with large datasets or data processing frameworks

  • Experience with additional programming languages such as TypeScript

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