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

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.

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.

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Preferred : • Advanced degree in Computer Science, Machine Learning, Robotics, or a related field. • Experience developing ML algorithms for autonomous vehicles or robotics applications. • ...

Machine Learning Tutor

Austin, TX · Remote

$18 - $40/hr

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Machine Learning Engineer

Austin, TX · On-site

$199K - $331K/yr

Utilize your fundamental understanding of neural networks and data science to develop models that serve as the foundation for machine learning applications for BCI. * Lead the team by performing at a ...

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Machine Learning Scientist information

See Austin, TX salary details

$77K

$139.7K

$195.7K

How much do machine learning scientist jobs pay per year?

As of Aug 2, 2026, the average yearly pay for machine learning scientist in Austin, TX is $139,739.00, according to ZipRecruiter salary data. Most workers in this role earn between $121,177.00 and $155,518.00 per year, depending on experience, location, and employer.

What is a Machine Learning Scientist job?

A Machine Learning Scientist researches, develops, and applies machine learning models to solve complex problems. They work on designing algorithms, improving model performance, and analyzing large datasets to extract valuable insights. Their role often involves experimenting with new techniques, optimizing existing models, and collaborating with engineers and data scientists to deploy solutions. Machine Learning Scientists typically have expertise in statistics, mathematics, and programming languages like Python. They work in industries such as healthcare, finance, and technology to drive innovation using artificial intelligence.

What are the typical daily tasks and collaboration opportunities for a Machine Learning Scientist?

A typical day for a Machine Learning Scientist involves collecting and analyzing large datasets, designing and training machine learning models, and evaluating model performance to ensure accuracy and reliability. You'll often collaborate with data engineers, software developers, and domain experts to define project goals, prepare data, and integrate solutions into production systems. Regular team meetings, code reviews, and brainstorming sessions are common, fostering an environment of shared learning and problem-solving. This collaborative structure not only enhances project outcomes but also offers valuable opportunities for continuous professional growth and skill development.

What are the key skills and qualifications needed to thrive in the Machine Learning Scientist position, and why are they important?

To thrive as a Machine Learning Scientist, you need strong skills in mathematics, statistics, programming (typically in Python or R), and a graduate degree in computer science, data science, or a related field. Expertise in machine learning frameworks (such as TensorFlow, PyTorch, or scikit-learn), proficiency with data processing tools, and experience with cloud platforms (like AWS or GCP) are commonly required; certifications in these can be advantageous. Critical thinking, problem-solving, and effective communication are important soft skills for collaborating with cross-functional teams and conveying complex concepts. These abilities enable Machine Learning Scientists to build effective models, deliver actionable insights, and drive innovation within organizations.

What are the most commonly searched types of Machine Learning Scientist jobs in Austin, TX? The most popular types of Machine Learning Scientist jobs in Austin, TX are:
What are popular job titles related to Machine Learning Scientist jobs in Austin, TX? For Machine Learning Scientist jobs in Austin, TX, the most frequently searched job titles are:
What job categories do people searching Machine Learning Scientist jobs in Austin, TX look for? The top searched job categories for Machine Learning Scientist jobs in Austin, TX are:
What cities near Austin, TX are hiring for Machine Learning Scientist jobs? Cities near Austin, TX with the most Machine Learning Scientist job openings:
Infographic showing various Machine Learning Scientist job openings in Austin, TX as of July 2026, with employment types broken down into 60% Full Time, 20% Temporary, and 20% Contract. Highlights an 80% In-person, and 20% Remote job distribution, with an average salary of $139,739 per year, or $67.2 per hour.

Senior Machine Learning Scientist - Agentic Experience

Expedia

Austin, TX

$299K/yr

Full-time

Medical, Dental, Vision, PTO

Re-posted 2 days ago


Expedia Group rating

7.9

Company rating: 7.9 out of 10

Based on 24 frontline employees who took The Breakroom Quiz

6th of 11 rated travel agencies


Job description

At Expedia Group, we help travelers explore the world, one journey at a time. As a global travel company powered by passionate people, trusted partnerships, and leading technology, we connect travelers, partners, and advertisers through our consumer brands, B2B network, and travel advertising business.


Here, you'll do meaningful work that helps millions of people discover, book, and experience travel with more ease, confidence, and joy. Our five Behaviors-Traveler First, Think Big, Operate with Excellence, Ownership Mindset, and Succeed Together-help foster a supportive environment where people can grow their careers and have the flexibility, benefits, and support to do their best work. Join us and build for travelers everywhere.

Introduction to the Team:

Expedia Technology teams partner with our Product teams to create innovative products, services, and tools to deliver high-quality experiences for travelers, partners, and our employees. A singular technology platform powered by data and machine learning provides secure, differentiated, and personalized experiences that drive loyalty and traveler satisfaction.

The Traveler Discovery & Planning team at Expedia is at the forefront of innovation in AI-driven agentic systems. We're dedicated to enhancing customer experiences, increasing engagement, and strengthening traveler relationships through cutting-edge machine learning solutions. Our work directly impacts millions of travelers worldwide, shaping their journey from dreaming to booking and beyond.

Join a team that's focused on Agentic Experiences revolutionizing traveler experiences through autonomous, intelligent agent systems. From building cutting-edge conversational AI that anticipates traveler needs to developing proactive solutions for personalized trip planning, your work will shape the future of travel assistance and directly impact millions of users worldwide. This is a rare opportunity to build foundational systems in a high-impact domain, backed by Expedia's AI-first vision.

In this role, you will:

  • Design, build, and evaluate multi-step agentic AI systems, including autonomous agents capable of planning, tool use, memory management, and multi-agent collaboration

  • Research and implement state-of-the-art techniques in agentic architectures, such as ReAct, reflection loops, chain-of-thought prompting, and tool-augmented reasoning

  • Develop and maintain agent orchestration frameworks, defining how agents decompose tasks, delegate to sub-agents, and handle failure and recovery

  • Integrate large language models (LLMs) with external tools, APIs, databases, and code execution environments to enable real-world task completion

  • Define and own evaluation frameworks for agentic systems, measuring task success, reliability, latency, cost, and safety across diverse benchmarks and production scenarios

  • Collaborate closely with product, engineering, and research teams to translate business requirements into agentic system designs and deliver production-grade solutions

  • Identify and mitigate risks specific to agentic systems, including prompt injection, unintended actions, hallucination in long-horizon tasks, and unsafe tool use

  • Stay current with the rapidly evolving agentic AI landscape, synthesizing academic research and industry developments to inform the team's technical direction

  • Mentor junior ML engineers and scientists, providing technical guidance on agentic design patterns, LLM best practices, and experimentation methodology

Minimum Qualifications:

  • 8+ years of related industry experience

  • Demonstrated experience designing and deploying agentic or multi-step AI systems (e.g., ReAct, tool-calling agents, multi-agent pipelines) in production or research settings

  • Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow, or JAX); experience with LLM APIs and orchestration libraries (e.g., LangChain, LlamaIndex, or similar)

  • Experience integrating LLMs with external tools, APIs, and structured data sources for real-world task completion

  • Solid understanding of prompt engineering techniques including chain-of-thought, few-shot prompting, and structured output generation

  • Experience defining and running evaluation frameworks for ML systems, including offline benchmarking and production monitoring

Preferred Qualifications:

  • PhD, MS, or BS in Computer Science, Machine Learning, Statistics, Engineering, or a related field; or equivalent professional experience

  • Experience in the travel or e-commerce industry

  • Publications in top-tier ML conferences or journals

  • Patented Inventions, pending and issued

  • Contributions to open-source ML projects

  • Experience taking models from prototype to production in collaboration with Machine Learning Engineering teams

The total cash range for this position in San Jose is $187,000.00 to $261,500.00. Employees in this role have the potential to increase their pay up to $299,000.00, which is the top of the range, based on ongoing, demonstrated, and sustained performance in the role.The total cash range for this position in Seattle is $173,000.00 to $242,500.00. Employees in this role have the potential to increase their pay up to $277,000.00, which is the top of the range, based on ongoing, demonstrated, and sustained performance in the role.The total cash range for this position in Austin is $173,000.00 to $242,500.00. Employees in this role have the potential to increase their pay up to $277,000.00, which is the top of the range, based on ongoing, demonstrated, and sustained performance in the role.

Starting pay for this role will vary based on multiple factors, including location, available budget, and an individual's knowledge, skills, and experience. Pay ranges may be modified in the future.

Benefits and perks

Expedia Group offers benefits and perks designed to support employees and their families, including medical, dental, and vision coverage, paid time off, an Employee Assistance Program, wellness and travel reimbursement, travel discounts, and International Airlines Travel Agent Network (IATAN) membership. Learn more about life at Expedia Group at https://careers.expediggroup.com/life.


Accommodation requests

Expedia Group is committed to providing an inclusive and accessible recruiting experience. If you need an accommodation or adjustment due to a disability during the application or recruiting process, please submit a request at https://expedia.service-now.com/askeg?id=job_accommodation.


About Expedia Group

Expedia Group includes three flagship consumer brands - Expedia, Hotels.com, and Vrbo - along with a leading B2B travel business and travel advertising offerings. Across our brands and business, we help travelers explore the world with confidence and ease.


Important notice

Employment opportunities and job offers at Expedia Group will always come from Expedia Group's Talent Acquisition and hiring teams. Never share sensitive personal information unless you are confident of the recipient. Expedia Group does not extend job offers via email or messaging tools to individuals with whom we have not made prior contact. Our email domain is @expediagroup.com. The official place to find and apply for roles is https://careers.expediagroup.com/jobs/.


Equal Opportunity

Expedia is committed to creating an inclusive work environment with a diverse workforce. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, veteran status, or any other characteristic protected by law. This employer participates in E-Verify. The employer will provide the Social Security Administration (SSA) and, if necessary, the Department of Homeland Security (DHS) with information from each new employee's I-9 to confirm work authorization.

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