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Graduate Machine Learning Engineer Jobs in Texas

PayPal, Inc. seeks Machine Learning Engineer in Austin, TX Job Duties: Gather, analyze and implement high-impact statistical models and AI applications in various business functional areas, focusing ...

Overview Come join Intuit as a Staff Machine Learning Engineer! In this role, you'll work alongside AI scientists and machine learning engineers to create AI-powered experiences. You'll be expected ...

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 ...

Summary The Machine Learning Engineer designs and evolves enterprise AI systems and architectures that enable scalable, secure, and high-impact adoption across the organization. This role defines end ...

Summary The Machine Learning Engineer designs and evolves enterprise AI systems and architectures that enable scalable, secure, and high-impact adoption across the organization. This role defines end ...

... Machine Learning Engineer. This role will assist our Online Retail Decision Automation team by ... Preferred Qualifications PhD or Graduate degree with research/work experience using data science ...

... Machine Learning Engineer. This role will assist our Online Retail Decision Automation team by ... Preferred Qualifications PhD or Graduate degree with research/work experience using data science ...

... Machine Learning Engineer. This role will assist our Online Retail Decision Automation team by ... Preferred Qualifications PhD or Graduate degree with research/work experience using data science ...

Senior Machine Learning Engineer

Houston, TX · On-site

$117K - $154K/yr

The Machine Learning Engineer at Vitol has visibility and impact across the full project workflow: from working with business stakeholders to help define the project, to data collation and processing ...

Machine Learning Engineer Responsibilities: Develop machine learning workflows to enable an Azure-First approach to computer vision applications. Conduct POCs with different vendors in data science ...

Senior Machine Learning Engineer

Houston, TX

$117K - $154K/yr

The Machine Learning Engineer at Vitol has visibility and impact across the full project workflow: from working with business stakeholders to help define the project, to data collation and processing ...

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Graduate Machine Learning Engineer information

See Texas salary details

$29.3K

$120K

$180.3K

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

As of Jun 20, 2026, the average yearly pay for graduate machine learning engineer in Texas is $119,968.00, according to ZipRecruiter salary data. Most workers in this role earn between $94,600.00 and $144,400.00 per year, depending on experience, location, and employer.

What does a Graduate Machine Learning Engineer do?

A Graduate Machine Learning Engineer is an entry-level professional who designs, develops, and tests machine learning models and algorithms. They work with data scientists and engineers to preprocess data, train models, and deploy solutions to solve real-world problems. Their responsibilities often include coding in languages like Python, using libraries such as TensorFlow or PyTorch, and staying updated with the latest advancements in machine learning. This role serves as a starting point for a career in AI, providing hands-on experience in building and optimizing intelligent systems.

What are the key skills and qualifications needed to thrive as a Graduate Machine Learning Engineer, and why are they important?

To thrive as a Graduate Machine Learning Engineer, you need a solid foundation in computer science, mathematics (especially statistics and linear algebra), and proficiency in programming languages like Python, often supported by a relevant degree. Familiarity with machine learning frameworks (such as TensorFlow or PyTorch), version control systems (like Git), and experience with cloud platforms or data management tools are typically expected. Strong analytical thinking, problem-solving abilities, and effective communication help you collaborate and translate complex concepts into practical solutions. These skills and qualities are crucial for developing robust models, integrating them into real-world applications, and contributing effectively to multidisciplinary teams.

What are some common challenges faced by Graduate Machine Learning Engineers during their first year, and how can they overcome them?

Graduate Machine Learning Engineers often encounter challenges such as bridging the gap between academic knowledge and real-world application, working with large or messy datasets, and learning to collaborate within cross-functional teams. Adapting to production-level code standards and understanding existing codebases can also be demanding. To overcome these hurdles, it's helpful to seek mentorship from experienced colleagues, actively participate in code reviews, and invest time in learning best practices for data preprocessing and model deployment. Embracing continuous learning and open communication will ease the transition into the professional environment.

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

AspectGraduate Machine Learning EngineerData Scientist
Required CredentialsBachelor's or Master's in CS, Data Science, or related field; some internshipsBachelor's or Master's in Statistics, Data Science, or related field; often with experience
Work EnvironmentDeveloping ML models, coding, testing algorithmsAnalyzing data, creating visualizations, deriving insights
Employer & Industry UsageTech companies, startups, research labsFinance, healthcare, tech, consulting firms

While both roles involve working with data and algorithms, Graduate Machine Learning Engineers focus on developing and deploying machine learning models, often requiring coding and technical skills. Data Scientists analyze data to extract insights and inform decisions. The roles overlap in skills but differ in primary responsibilities and focus areas.

Infographic showing various Graduate Machine Learning Engineer job openings in Texas as of June 2026, with employment types broken down into 75% Full Time, 19% Part Time, 2% Temporary, and 4% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $119,968 per year, or $57.7 per hour.
Machine Learning Engineer

Machine Learning Engineer

PayPal

Austin, TX • On-site

Full-time

Medical, PTO

Posted 2 days ago


PayPal rating

6.8

Company rating: 6.8 out of 10

Based on 18 frontline employees who took The Breakroom Quiz

15th of 17 rated payment service providers


Job description

The Company

PayPal has been revolutionizing commerce globally for more than 25 years. Creating innovative experiences that make moving money, selling, and shopping simple, personalized, and secure, PayPal empowers consumers and businesses in approximately 200 markets to join and thrive in the global economy.

We operate a global, two-sided network at scale that connects hundreds of millions of merchants and consumers. We help merchants and consumers connect, transact, and complete payments, whether they are online or in person. PayPal is more than a connection to third-party payment networks. We provide proprietary payment solutions accepted by merchants that enable the completion of payments on our platform on behalf of our customers.

We offer our customers the flexibility to use their accounts to purchase and receive payments for goods and services, as well as the ability to transfer and withdraw funds. We enable consumers to exchange funds more safely with merchants using a variety of funding sources, which may include a bank account, a PayPal or Venmo account balance, PayPal and Venmo branded credit products, a credit card, a debit card, certain cryptocurrencies, or other stored value products such as gift cards, and eligible credit card rewards. Our PayPal, Venmo, and Xoom products also make it safer and simpler for friends and family to transfer funds to each other. We offer merchants an end-to-end payments solution that provides authorization and settlement capabilities, as well as instant access to funds and payouts. We also help merchants connect with their customers, process exchanges and returns, and manage risk. We enable consumers to engage in cross-border shopping and merchants to extend their global reach while reducing the complexity and friction involved in enabling cross-border trade.

Our beliefs are the foundation for how we conduct business every day. We live each day guided by our core values of Inclusion, Innovation, Collaboration, and Wellness. Together, our values ensure that we work together as one global team with our customers at the center of everything we do - and they push us to ensure we take care of ourselves, each other, and our communities.

Job Summary:

Job Description:

PayPal, Inc. seeks Machine Learning Engineer in Austin, TX

Job Duties: Gather, analyze and implement high-impact statistical models and AI applications in various business functional areas, focusing on but not limited to Natural Language Processing (NLP) models and Generative AI. Conduct quantitative and qualitative model validation in line with internal Model Risk Management Policy and industry standard to identify and report issues arising from model data, model design and model use. Maintain technical documentation of AI/ML model development and validation. Collaborate with business units and model developers to ensure model issues are agreed and remediated in a timely manner. Build effective relationship with stakeholders from various teams such as data science, engineering, product, customer service/complaints, compliance, audit. Research latest AI/ML advancements and explore opportunities for innovation. Partial telecommuting permitted from within a commutable distance.

Minimum Requirements: Master's degree, or foreign equivalent, in Computer Science, Engineering, Data Science, or a closely related field plus one year of experience in the job offered or a related occupation.

Special Skill Requirements:

1. Experience developing and deploying statistical model and data-driven applications using Python to analyze multi-terabyte datasets, generate actionable insights and support decision-making for business operation (1 year).

2. Experience analyzing and interpreting credit reports and credit data to derive business insights (1 year).

3. Experience querying, manipulating, and analyzing multi-terabyte datasets, including external bureau data, using SQL to enable advanced business analytics in large-scale operational environments (1 year).

4. Experience building interactive dashboard and data visualizations with Tableau/Looker Studio to communicate customer analytics to stakeholders (1 year).

5. Experience designing, implementing, and deploying machine learning models for business applications (1 year).

6. Experience extracting, transforming, and selecting meaningful features from credit datasets to improve model performance (1 year).

7. Experience conducting statistical analysis and hypothesis testing to uncover meaningful trends and generate actionable recommendations (1 year).

8. Experience working with Generative AI architectures, including Large Language Model (LLMs), to analyze, automate, and enhance internal tool process - such as developing NLP-driven transcription and summarization tools (1 year).

Additional Responsibilities & Preferred Qualifications:

EOE, including disability/vets.

The base pay for this role will depend on where you work and the relevant experience andexpertiseyou bring. The expected range of pay for this role by location is:

Primary Location | Pay Range:

Austin, TX | Salary: $117,500.00-199,500.00 per annum. 40 hours per week; M-F, 9:00 a.m. to 5:00 p.m.

Additionalcompensation for this role may include an annual performance bonus, equity, or other incentive compensation, as applicable.

Must be legally authorized to work in the U.S. without sponsorship.

Subsidiary:

PayPal

Travel Percent:

0

PayPal does not charge candidates any fees for courses, applications, resume reviews, interviews, background checks, or onboarding. When making an application directly, we will never ask you to share passwords, one-time passcodes (OTP), or verification codes. Any such request is a red flag and likely part of a scam. All communication regarding your application will come from official PayPal email domains. If you suspect fraudulent activity, please report it immediately. To learn more about how to identify and avoid recruitment fraud please visit https://careers.pypl.com/contact-us.

For the majority of employees, PayPal's balanced hybrid work model offers 3 days in the office for effective in-person collaboration and 2 days at your choice of either the PayPal office or your home workspace, ensuring that you equally have the benefits and conveniences of both locations.

Our Benefits:

At PayPal, we're committed to building an equitable and inclusive global economy. And we can't do this without our most important asset-you. That's why we offer comprehensive, choice-based programs, to support all aspects of personal wellbeing-physical, emotional, and financial-delivering meaningful value where it matters most.We strive to create a flexible, balanced work culture with a holistic approach to benefits, including generous paid time off, healthcare coverage for you and your family, and resources to create financial security and support your mental health.

Who We Are:

Click Here to learn more about our culture and community.

Commitment to Diversity and Inclusion

PayPal provides equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, pregnancy, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state, or local law. In addition, PayPal will provide reasonable accommodations for qualified individuals with disabilities. If you are unable to submit an application because of incompatible assistive technology or a disability, please contact us atpaypalglobaltalentacquisition@paypal.com.

Belonging at PayPal:

Our employees are central to advancing our mission, and we strive to create an environment where everyone can do their best work with a sense of purpose and belonging. Belonging at PayPal means creating a workplace with a sense of acceptance and security where all employees feel included and valued. We are proud to have a diverse workforce reflective of the merchants, consumers, and communities that we serve, and we continue to take tangible actions to cultivate inclusivity and belonging at PayPal.

Any general requests for consideration of your skills, please Join our Talent Community.

We know the confidence gap and imposter syndrome can get in the way of meeting spectacular candidates. Please don't hesitate to apply.


What PayPal employees say

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Benefits

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About PayPal

Sourced by ZipRecruiter

PayPal has remained at the forefront of the digital payment revolution for more than 20 years. By leveraging technology to make financial services and commerce more convenient, affordable, and secure, the PayPal platform is empowering more than 400 million consumers and merchants in more than 200 markets to join and thrive in the global economy. For more information, visit paypal.com. PayPal provides equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, pregnancy, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state or local law. In addition, PayPal will provide reasonable accommodations for qualified individuals with disabilities. If you are unable to submit an application because of incompatible assistive technology or a disability, please contact us at paypalglobaltalentacquisition@paypal.com.

Industry

Software development

Company size

10,000+ Employees

Headquarters location

San Jose, CA, US

Year founded

1998

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