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

Apple

Senior Machine Learning Engineer

Austin, TX

$184K - $324K/yr

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 ...

Apple

Senior Machine Learning Engineer

Austin, TX

$184K - $324K/yr

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 ...

Apple

Senior Machine Learning Engineer

Austin, TX

$184K - $324K/yr

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 ...

Avride

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 ...

Avride

Senior / Staff Machine Learning Engineer

Austin, TX

$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 ...

ForeFlight

Staff Machine Learning Engineer

Austin, TX · On-site +1

$208K - $255K/yr

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 ...

Rokt

Senior Machine Learning Engineer

Austin, TX · On-site

$335K - $400K/yr

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 ...

Rokt

Senior Machine Learning Engineer

Austin, TX · On-site

$335K - $400K/yr

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 ...

Rokt

Senior Machine Learning Engineer

Austin, TX · On-site +1

$335K - $400K/yr

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 ...

Roku

Senior Machine Learning Engineer

Austin, TX · On-site

$121K - $160K/yr

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 ...

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All JobsScientific Machine Learning JobsScientific Machine Learning Jobs in Austin, TX

Scientific Machine Learning information

See Austin, TX salary details

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How much do scientific machine learning jobs pay per hour?

As of Aug 9, 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 job categories do people searching Scientific Machine Learning jobs in Austin, TX look for? The top searched job categories for Scientific Machine Learning jobs in Austin, TX 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:
Scientific Machine Learning jobs near you
Infographic showing various Scientific Machine Learning job openings in Austin, TX as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 22% Part Time, 1% Temporary, and 3% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $64,897 per year, or $31.2 per hour.

Senior Machine Learning Engineer (Active Secret Clearance)

Striveworks

Austin, TX • On-site

$185K - $230K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 23 days ago

Job description

"In 36 months, agentic AI systems will be an operating reality across major institutions. We intend to be central to it." - Dr. Jim Rebesco, Cofounder and CEO, Striveworks
The government's demand for AI is growing far faster than the systems required to support it. Fewer than 15% of federal AI programs have reached sustained production, despite billions of dollars invested. The models perform in testing, but they degrade in the real world. And when performance drops, trust goes with it.
Striveworks was built to solve that problem.
What you'll build
Since 2018, we have delivered the most trusted AI systems operating in real-world use cases-providing a layer of assurance underneath hundreds of deployed models that monitors performance, manages drift, and sustains systems long after they leave the lab.
As a Senior Machine Learning Engineer, you will be a core contributor to both customer-driven projects and the enduring products of the company. Working directly with customers, data scientists, software engineers, and DevOps engineers, you'll define requirements and orchestrate complex data engineering pipelines. You'll also develop machine learning models and custom analytics applied to image, video, text, geospatial, time series, and structured data. Your work will inform the future of Chariot, our proprietary AI operations platform, and it extends to the field, with mission-critical deployments, direct customer contact, and insights that shape what we build next.
What it's like here
We lead with trust, treat each other with respect, and use candor consistently, kindly, and constructively. We care deeply about our work, and we find genuine satisfaction in doing it well. Above all, we take ownership-because we feel the weight of collective results personally. We are looking for people who share these values and are eager to put them into practice.
What we're looking for
  • A BS degree in computer science, machine learning, or a related discipline and 6+ years relevant experience
  • Demonstrated experience delivering data-centric systems
  • Proficiency in programming languages and libraries common to machine learning; excellence in Python is essential, as is knowledge of TensorFlow, PyTorch, and/or scikit-learn
  • Proficiency in software engineering fundamentals to include algorithms, data structures, design patterns, and at least one systems programming language
  • Proficiency with modern software engineering tools and processes
  • Active Secret (or above) US security clearance and US citizenship

The following isn't required, but we'd love to see it:
  • Advanced degree in data science, machine learning, computer science, or a related discipline
  • Knowledge of relevant architectures and design patterns for client-server systems
  • Experience implementing and deploying software into containerized or cloud environments
  • Experience with a variety of unstructured data types
  • Experience delivering technology solutions in secure government environments
  • Experience building AI agents, agentic workflows, or agentic systems
  • Experience defining, scoping, planning, and delivering complex, production-level technical solutions
  • Experience leading, managing, or mentoring small, cross-functional engineering teams

You will be hybrid out of our Austin, Texas, office. This role requires travel up to 25% of the time.
Compensation
The anticipated base pay range for this position is $185,000-$230,000/year. Striveworks' total compensation package includes a competitive base salary, equity grants, and cash bonuses.
Benefits include:
  • Medical/dental/vision insurance
  • Voluntary life, long-term disability, accident, and hospital indemnity insurance
  • HSA and FSA (including dependent care FSA) plans
  • 401(k) plan
  • Unlimited PTO
  • Paid parental leave

Ready to build systems that work for a mission that matters? Let's talk.
Striveworks is an Equal Opportunity Employer and does not discriminate in employment on the basis of race, color, religion, belief, sex (including pregnancy and gender identity or expression), national origin, social or ethnic origin, political affiliation, sexual orientation, marital status, disability, genetic information, age, membership in an employee organization, retaliation, parental status, military service, or other non-merit factors. Striveworks will not tolerate discrimination or harassment of any kind.
If you require assistance or a reasonable accommodation in the application process, please contact People Operations at hr@striveworks.us.
In compliance with federal law, all persons hired will be required to verify their identity and eligibility to work in the United States and to complete an employment eligibility verification form upon hire.
Striveworks is a participating employer in the E-Verify program.

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