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

Senior Machine Learning Engineer

Austin, TX

$184K - $324K/yr

  • Medical

  • Dental

  • Retirement

Preferred Qualifications PhD or Graduate degree with research/work experience using data science ... Experience building data processing pipelines and large scale machine learning systems with ...

Senior Machine Learning Engineer

Austin, TX

$184K - $324K/yr

  • Medical

  • Dental

  • Retirement

Preferred Qualifications PhD or Graduate degree with research/work experience using data science ... Experience building data processing pipelines and large scale machine learning systems with ...

Senior Machine Learning Engineer

Austin, TX

$184K - $324K/yr

  • Medical

  • Dental

  • Retirement

Preferred Qualifications PhD or Graduate degree with research/work experience using data science ... Experience building data processing pipelines and large scale machine learning systems with ...

Senior / Staff Machine Learning Engineer

Austin, TX · On-site

$124K - $171K/yr

Advanced degree in Computer Science, Machine Learning, Robotics, or a related field. * Experience developing ML algorithms for autonomous vehicles or robotics applications. * Familiarity with neural ...

Staff Machine Learning Engineer

Austin, TX · On-site +1

$208K - $255K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Bachelor's or Master's degree in Computer Science, Machine Learning, Electrical Engineering, Linguistics, or related field. * 3+ years of experience in speech recognition, audio ML, or applied ...

Senior Machine Learning Engineer

Austin, TX · On-site

$335K - $400K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

PhD or Master's in Computer Science, Statistics, Mathematics, or related field with specialization ... grade machine learning systems, spanning model training, tuning, deployment, serving, and ...

Senior Machine Learning Engineer

Austin, TX · On-site +1

$335K - $400K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

PhD or Master's in Computer Science, Statistics, Mathematics, or related field with specialization ... grade machine learning systems, spanning model training, tuning, deployment, serving, and ...

Senior Machine Learning Engineer

Austin, TX · On-site

$335K - $400K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

PhD or Master's in Computer Science, Statistics, Mathematics, or related field with specialization ... grade machine learning systems, spanning model training, tuning, deployment, serving, and ...

Senior Machine Learning Engineer

Austin, TX · On-site

$121K - $160K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

Bachelors, Masters, or PhD in Computer Science, Statistics, or a related field * 5 years of experience in applied machine learning on real use cases * Proficient coding skills and strong software ...

Machine Learning Engineer, OIS-Core Engine

Austin, TX · On-site

$143.70 - $194.40/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

... Science, Engineering, Mathematics, or a related field * - Experience programming with at least one software programming language Preferred Qualifications * - 3+ years of full software development ...

Showing results 41-60

Scientific Machine Learning information

See Austin, TX salary details

$13

$31

$51

How much do scientific machine learning jobs pay per hour?

As of Aug 13, 2026, the average hourly pay for scientific machine learning in Austin, TX is $31.20, according to ZipRecruiter salary data. Most workers in this role earn between $19.04 and $39.81 per hour, depending on experience, location, and employer.

What is scientific machine learning?

Scientific machine learning (SciML) is an interdisciplinary field that combines principles from machine learning and scientific computing to solve complex scientific and engineering problems. It involves developing algorithms and models that can learn from data and physical laws, such as differential equations, to make predictions, optimize systems, or gain insights into phenomena. SciML is widely used in areas like physics, biology, climate science, and engineering, enabling researchers to accelerate simulations and make data-driven discoveries. The field often leverages both traditional numerical methods and modern machine learning techniques, making it a rapidly evolving area of research.

What are some common challenges faced by professionals in scientific machine learning, and how can they be addressed?

Professionals in Scientific Machine Learning often encounter challenges such as integrating domain-specific scientific knowledge with machine learning models, managing large and complex datasets, and ensuring that models are interpretable and physically consistent. Collaboration with domain experts and interdisciplinary teams is essential to bridge knowledge gaps and validate results. To address these challenges, it is helpful to invest time in understanding the underlying scientific principles, keep up-to-date with advancements in both machine learning and scientific fields, and utilize specialized tools and frameworks designed for scientific data.

What are the key skills and qualifications needed to thrive as a scientific machine learning professional, and why are they important?

To thrive as a Scientific Machine Learning professional, you need a strong background in mathematics, statistics, programming (often Python), and domain-specific scientific knowledge, typically with a graduate degree in a STEM field. Proficiency in machine learning frameworks (such as TensorFlow or PyTorch), scientific computing tools (like NumPy, SciPy), and experience with high-performance computing are commonly required. Critical thinking, problem-solving, and collaborative communication are vital soft skills for designing experiments and interpreting complex data. These skills ensure robust, reproducible results and the ability to bridge scientific inquiry with advanced computational methods.

What is the difference between Scientific Machine Learning vs Data Scientist?

AspectScientific Machine LearningData Scientist
Required credentialsAdvanced degrees in CS, ML, or related fields; knowledge of scientific computingDegree in CS, statistics, or related fields; strong analytical skills
Work environmentResearch labs, academia, industry R&D teamsBusiness analytics, tech companies, consulting firms
Industry usageResearch, scientific computing, engineering simulationsBusiness insights, predictive modeling, data analysis

Scientific Machine Learning focuses on integrating scientific knowledge with machine learning techniques for research and engineering applications. Data Scientists analyze data to extract insights and build predictive models for business or operational purposes. While both roles require strong technical skills, Scientific Machine Learning emphasizes scientific computing and domain-specific modeling, whereas Data Scientists focus on data analysis and visualization.

What are popular job titles related to Scientific Machine Learning jobs in Austin, TX? For Scientific Machine Learning jobs in Austin, TX, the most frequently searched job titles are:
What cities near Austin, TX are hiring for Scientific Machine Learning jobs? Cities near Austin, TX with the most Scientific Machine Learning job openings:
Infographic showing various Scientific Machine Learning job openings in Austin, TX as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 21% Part Time, 1% Temporary, and 3% Contract. Highlights an 89% Physical, 2% Hybrid, and 9% Remote job distribution, with an average salary of $64,897 per year, or $31.2 per hour.

Senior Machine Learning Engineer

Apple

Austin, TX

$184K - $324K/yr

Full-time

Medical, Dental, Retirement

Re-posted 5 days ago


Apple rating

8.0

Company rating: 8.0 out of 10

Based on 677 frontline employees who took The Breakroom Quiz

7th of 30 rated technology retailers


Job description

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 diversity of those people and their ideas that inspires the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts. At Apple, inclusion is a shared responsibility, and we work together to foster a culture where everyone belongs and is inspired to do their best work.
Here on the Apple Store Online team, we are responsible for Apple’s largest store. Our main goal is to deliver a magical, personal digital experience where customers can shop, buy and learn everything Apple, wherever they are. Each customer should feel like they are our only customer and our job is to set the bar for the experience they receive. To run such an extraordinary store, it takes extraordinary people, and we are looking for someone to help us do extraordinary things.
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 develop the next generation of algorithms used to drive the Apple Online experience! The role spans central areas of our Apple Online Store including developing models for product search, recommendation systems (e.g. ranking, page generation), personalization (e.g. evidence, messaging, marketing), Generative AI and optimize Apple-wide systems & infrastructure. As a member of the fast-paced team, you will have the outstanding and great opportunity to work on new projects and craft upcoming products that will delight and encourage millions of Appleʼs customers ever day.
Description
To be successful, candidates will need a machine learning background, proven software development skills, a love of learning. They will also need to be able to collaborate with multi-functional teams, including researchers, engineers, data scientists/analysts, and product managers, to help develop and implement machine learning algorithms and testing workflows.","responsibilities":"Collaborate with other MLEs to build scalable, production-ready ML solutions, taking algorithms from initial concept through to deployment.
Give to the ongoing improvement of our ML infrastructure and tooling.
Engage in continuous learning and development, staying up-to-date with the latest advances in machine learning and software engineering.
Mentor junior MLEs on the team to ensure best practices are followed.
Preferred Qualifications
PhD or Graduate degree with research/work experience using data science techniques (including but not limited to Computer Science, Statistics, Mathematics, etc).
Experience in Recommender Systems, Personalization, Search, Computational Advertising or Natural Language Processing including RAG based Generative AI and transformer architecture.
Skilled in communication, problem solving, critical thinking.
Experience using Deep Learning, Bandits, Probabilistic Graphical Models, or Reinforcement Learning in real applications a plus.
Experience with Spark, TensorFlow, Keras, and PyTorch a plus
Minimum Qualifications
Bachelorʼs degree in Computer Science, Statistics, Mathematics with equivalent experience.
5+ years of related experience building high throughput scalable applications or building machine learning models.
Proficiency in one or more object-oriented programming languages such as Python, Java, C++ and experience building distributed systems.
Experience building data processing pipelines and large scale machine learning systems with experience in big data technologies like Spark, SQL, Snowflake/Hadoop, etc.
Skilled in communication, problem solving, critical thinking Attention to detail, data accuracy and quality of output.
Pay & Benefits
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $184,700 and $324,800, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

What Apple employees say

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About Apple

Sourced by ZipRecruiter

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976