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Machine Learning Engineer Python Jobs in Leander, TX

Sr Machine Learning Engineer

Austin, TX · On-site

$121K - $160K/yr

PayPal, Inc. seeks Sr Machine Learning Engineer in Austin, TX Job Duties: Evaluate and validate ... Build scalable systems with Python and cloud platforms, and architect end-to-end pipelines for real ...

As a Senior Machine Learning Engineer, you'll own impactful problems end-to-end-from data ... Proficiency in Python and experience with at least one major ML framework (e.g. PyTorch, TensorFlow)

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 ...

Broad proficiency in programming languages common to machine learning (excellence in Python is essential, as is knowledge of libraries like TensorFlow, PyTorch, and scikit-learn) and systems ...

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Machine Learning Engineer Python information

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$22K

$133.7K

$193.5K

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

As of Jun 25, 2026, the average yearly pay for machine learning engineer python in Leander, TX is $133,743.00, according to ZipRecruiter salary data. Most workers in this role earn between $105,600.00 and $157,200.00 per year, depending on experience, location, and employer.

What are some common challenges faced by Machine Learning Engineers working with Python, and how can they be addressed?

Machine Learning Engineers using Python often encounter challenges such as managing large datasets, ensuring efficient model deployment, and maintaining reproducibility of experiments. Handling data pipelines and model versioning can be complex, especially as projects scale. To address these issues, engineers typically use tools like Pandas and Dask for data handling, Docker for containerization, and MLflow or DVC for tracking experiments and models. Collaborating closely with data engineers, software developers, and product teams is also essential to streamline workflows and ensure models are production-ready.

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

To thrive as a Machine Learning Engineer Python, you need a solid background in computer science, statistics, and mathematics, along with proficiency in Python programming and machine learning concepts. Familiarity with frameworks such as TensorFlow, PyTorch, Scikit-learn, and experience with cloud platforms or MLOps tools are highly valued, as are certifications like Google Professional Machine Learning Engineer. Strong problem-solving abilities, communication skills, and a collaborative mindset help set you apart in this field. These skills enable engineers to design, implement, and deploy effective machine learning solutions that address real-world challenges in dynamic, team-oriented environments.

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

AspectMachine Learning Engineer PythonData Scientist
Required CredentialsBachelor's/Master's in CS, Data Science, or related; Python skills; ML certificationsBachelor's/Master's in Statistics, CS, or related; Python/R skills; Data analysis certifications
Work EnvironmentDevelops scalable ML models, deploys algorithms, collaborates with engineering teamsAnalyzes data, builds models, interprets results, communicates insights
Employer & Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research institutions

While both roles require Python proficiency and data skills, Machine Learning Engineers focus on building and deploying scalable ML models, whereas Data Scientists analyze data and generate insights. The roles often overlap but differ in their primary focus and responsibilities.

What is a Machine Learning Engineer Python?

A Machine Learning Engineer Python is a professional who uses the Python programming language to design, build, and deploy machine learning models and systems. They work with large datasets, develop algorithms, and use Python libraries such as TensorFlow, scikit-learn, and PyTorch to solve complex problems. Their responsibilities also include preprocessing data, training models, evaluating performance, and integrating solutions into production environments. Machine Learning Engineers often collaborate with data scientists, software engineers, and business stakeholders to create scalable and efficient machine learning applications.
What are popular job titles related to Machine Learning Engineer Python jobs in Leander, TX? For Machine Learning Engineer Python jobs in Leander, TX, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Python jobs in Leander, TX look for? The top searched job categories for Machine Learning Engineer Python jobs in Leander, TX are:
What cities near Leander, TX are hiring for Machine Learning Engineer Python jobs? Cities near Leander, TX with the most Machine Learning Engineer Python job openings:
Sr Machine Learning Engineer

Sr Machine Learning Engineer

PayPal, Inc.

Austin, TX • On-site

$121K - $160K/yr

Full-time

Medical, PTO

Posted 13 days ago


PayPal rating

6.8

Company rating: 6.8 out of 10

Based on 18 frontline employees who took The Breakroom Quiz

16th of 18 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 Sr Machine Learning Engineer in Austin, TX
Job Duties: Evaluate and validate high-impact statistical and AI/ML models across key business areas. Perform comprehensive quantitative and qualitative model validation in alignment with internal Model Risk Management (MRM) Policy and industry standards. Assess model data integrity, design soundness, and performance robustness to identify and report potential risks and deficiencies. Provide risk oversight on the engineering, automation, and production deployment of sophisticated machine learning models. Build scalable systems with Python and cloud platforms, and architect end-to-end pipelines for real-time data ingestion, model serving, and monitoring. Lead technical projects, coordinate project roadmaps, and mentor junior engineers while integrating cutting-edge methods in deep learning and generative AI. Ensure system reliability, regulatory compliance, and technical innovation through collaboration with DevOps, IT, and business partners. Drive transformative change across products and services through continuous improvement, advanced model tuning, and implementation of system-wide best practices for performance, scalability, and ethical AI use. Partial telecommuting permitted from within a commutable distance.
Minimum Requirements: Master's degree, or foreign equivalent, in Data Science, Computer Science, Business Analytics, or a closely related field plus two years of experience in the job offered or a related occupation.
Special Skill Requirements:
1. Experience designing and implementing scalable machine learning models using algorithms such as logistic regression, random forests, gradient boosting, and time series models to solve business problems (2 years).
2, Experience utilizing deep learning and Generative AI architectures, including CNNs, RNNs, and large language models (LLMs), to enhance automation and decision-making (2 years).
3. Experience conducting exploratory data analysis (EDA), statistical modeling, and visualization to identify trends, detect anomalies, and inform model improvements (2 years).
4. Experience programming in Python for model development, validation, and automation using libraries such as pandas, scikit-learn, TensorFlow, and PyTorch (2 years).
5.Experience writing and optimizing complex SQL queries for data extraction, transformation, and analytics in large-scale environments (2 years).
6. Experience developing, validating, and maintaining statistical and AI/ML models for risk management, fraud detection, AML, and compliance in alignment with Model Risk Management (MRM) standards (2 years).
7. Experience performing comprehensive model validation, including data quality assessment, benchmarking, back-testing, and performance evaluation (2 years).
8. Experience preparing model documentation, validation reports, and findings in compliance with internal governance and regulatory standards (2 years).
Additional Responsibilities & Preferred Qualifications:
EOE, including disability/vets.
The base pay for this role will depend on where you work and the relevant experience and expertise you 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.
Additional compensation 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 at paypalglobaltalentacquisition@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.

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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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