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Machine Learning Engineer Opt Jobs in Austin, TX

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 ...

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 ...

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 ...

Currently, we are looking for entry-level software programmers, IT enthusiasts, Python/Java ... Preferred Skills NLP, Deep Learning, Data visualization, Scala, Django. Our candidates always get ...

Senior Machine Learning Engineer

Austin, TX

$103K - $142K/yr

Comscore, Total Visits, March 2025) Day to Day As a Senior Machine Learning Engineer on our Sourcing team, you will work on developing and deploying ML and AI solutions in production. You'll be ...

Senior Machine Learning Engineer

Austin, TX · On-site +1

$121K - $160K/yr

The Role As a Senior Machine Learning Engineer at Striveworks, you'll be challenged-and trusted-on day one to be a core contributor to both the customer-driven projects and the enduring products of ...

Senior Machine Learning Engineer

Austin, TX · On-site

$121K - $160K/yr

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

We are looking for a Machine Learning Engineer to help us design and deliver CX solutions that provide our clients with a beautiful customer journey that achieves results. At PTP we value aptitude ...

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

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

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

Senior / Staff 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 ...

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Machine Learning Engineer Opt information

See Austin, TX salary details

$31.2K

$127.6K

$191.8K

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

As of Jun 19, 2026, the average yearly pay for machine learning engineer opt 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 are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models into production environments. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, reliable systems that organizations can use to make predictions or automate tasks. Their responsibilities include data preprocessing, choosing appropriate algorithms, model training, and ensuring the model's performance in real-world applications. Machine Learning Engineers often collaborate with data scientists, data engineers, and product teams to deliver intelligent solutions.

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

AspectMachine Learning Engineer OptData Scientist
Required CredentialsBachelor's or Master's in CS, AI, or related fields; certifications in ML toolsBachelor's or Master's in CS, Statistics, or related fields; data analysis certifications
Work EnvironmentDevelops, tests, and deploys ML models in production systemsAnalyzes data, builds models, and provides insights for decision-making
Employer & Industry UsageTech companies, AI startups, e-commerce, financeResearch institutions, tech firms, consulting, finance
Common Search & ComparisonOften compared for technical skills and deployment focusCompared for data analysis and business insights

Machine Learning Engineers Opt focus on deploying scalable ML models in production environments, while Data Scientists primarily analyze data and develop models for insights. Both roles require strong technical skills, but their core responsibilities differ in application and deployment.

Is a machine learning engineer still in demand?

Yes, machine learning engineers are in high demand due to the growing adoption of AI and data-driven solutions across industries. They are sought after for their skills in programming, data analysis, and familiarity with tools like Python, TensorFlow, and cloud platforms, making this a strong career choice for those with relevant expertise.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as AI advances because they develop and refine AI models, requiring specialized skills in programming, data analysis, and domain knowledge. Jobs that involve complex problem-solving, creativity, and emotional intelligence, such as healthcare professionals, educators, and skilled tradespeople, are also expected to persist despite AI automation. Continuous learning and adapting to new tools and technologies will be essential for job security across many fields.

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 a solid background in mathematics, statistics, and programming (especially Python), typically supported by a degree in computer science, engineering, or a related field. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch), data processing tools, and cloud platforms, along with relevant certifications, is highly valuable. Strong problem-solving ability, collaboration, and effective communication are standout soft skills in this role. These skills and qualities ensure the successful development, deployment, and integration of machine learning solutions that drive business value.

What is a $900,000 AI job?

A $900,000 AI-related job typically refers to high-level roles such as senior machine learning engineers, AI research directors, or chief AI officers, often in large tech companies or specialized firms. These positions usually require advanced skills in machine learning, deep learning, and data science, along with extensive experience and leadership responsibilities.

What are some common challenges Machine Learning Engineers face when deploying models to production environments?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, handling data drift, and integrating models seamlessly with existing systems when deploying to production. Monitoring model performance in real time and retraining models as new data becomes available are also critical tasks. Collaboration with data engineers and DevOps teams is essential to address infrastructure and deployment hurdles while maintaining model accuracy and reliability.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-paying industries such as finance or tech, can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially at large tech companies or startups with significant funding.
What job categories do people searching Machine Learning Engineer Opt jobs in Austin, TX look for? The top searched job categories for Machine Learning Engineer Opt jobs in Austin, TX are:
What cities near Austin, TX are hiring for Machine Learning Engineer Opt jobs? Cities near Austin, TX with the most Machine Learning Engineer Opt job openings:
Machine Learning Engineer

Machine Learning Engineer

PayPal, Inc.

Austin, TX • On-site

Full-time

Medical, PTO

This job post has expired today. Applications are no longer accepted.


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 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.

What PayPal employees say

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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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