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

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 ...

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 ...

... 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 ...

Founded by data scientists and engineers, Striveworks set out to make the journey from deployment ... The Role As a Staff Machine Learning Engineer at Striveworks, you will be challenged-and trusted-on ...

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 ...

Senior Machine Learning Engineer

Austin, TX · On-site

$121K - $160K/yr

Minimum Qualifications Bachelorʼs degree in Computer Science, Statistics, Mathematics with ... Experience building data processing pipelines and large scale machine learning systems with ...

Senior Machine Learning Engineer

Austin, TX

$121K - $160K/yr

We use Machine Learning, Reinforcement Learning, AI, Control and Optimization Systems, and Auction ... Partner with product managers, data scientists, and other engineers to deliver impactful solutions

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Scientific Machine Learning information

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$13

$31

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How much do scientific machine learning jobs pay per hour?

As of Jul 21, 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 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:
Infographic showing various Scientific Machine Learning job openings in Austin, TX as of July 2026, with employment types broken down into 1% As Needed, 72% Full Time, 25% Part Time, 1% Temporary, and 1% Contract. Highlights an 89% Physical, 1% Hybrid, and 10% Remote job distribution, with an average salary of $64,897 per year, or $31.2 per hour.
Machine Learning Engineer (Active Secret Clearance)

Machine Learning Engineer (Active Secret Clearance)

Striveworks

Austin, TX • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 27 days ago


Job description

Build, Deploy, and Maintain AI for an Unpredictable World
Striveworks helps organizations harness the power of artificial intelligence to solve real-world national security and business challenges by serving as the command center between data, models, and business outcomes. Founded by data scientists and engineers, Striveworks set out to make the journey from deployment to ongoing optimization simple and effective.
With Striveworks, organizations aren't just deploying AI-they're building systems that remain reliable, adaptable, and ready to scale in an unpredictable world. Mission-critical operations require models that perform where they're deployed, scale as workloads grow, and adapt rapidly as AI capabilities advance. Striveworks meets these demands-increasing reliability and performance while lowering costs and enabling confident, data-driven decision-making in dynamic environments.
The Role
As a 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 the company. You will represent Striveworks as a technology builder on projects and solutions that leverage Chariot, our proprietary AI operations (AIOps) platform, and you will inform and contribute to future capabilities of that platform. You will inform, envision, and help extend Striveworks' core software products. You will work alongside data scientists, software engineers, and DevOps engineers to transform machine learning models into operational capabilities.
You're right for this opportunity if you value and possess technical expertise and enjoy pushing the boundaries of your own capabilities. You're outcome-driven and are passionate about applying both software engineering and data science to solve real-world problems. You know that building customer-centric solutions, communicating clearly, and capturing repeatable value into productized capabilities are all important.
Your day-to-day will include:
  • Developing machine learning models and custom analytics that are applied to image, video, text, geospatial, time series, and structured data
  • Orchestrating and automating complex data engineering and analytic pipelines
  • Envisioning, specifying, and, at times, designing and implementing core product functionality
  • Conducting mission-critical fieldwork in support of customers and other stakeholders

This position offers a hybrid/on-site work environment at our office in northwest Austin, TX. You will be expected to travel up to 30% of the time.
The Right Fit
In addition to the specific skills and expertise detailed below, we are looking for individuals who share our values. Sharing a set of values allows us to move at the speed of trust.
We value a high-trust work environment where people respect each other and use candor kindly and constructively. We value work that intersects passion and perseverance, we geek out about the potential of our contributions, and we find joy in working hard on things that matter. Finally, we value taking ownership, having agency, and feeling individual responsibility for collective results.
Here's what we're looking for:
  • BS degree in computer science, machine learning, or a related discipline and 2+ years of relevant experience
  • Experience contributing to data-centric systems (e.g., data engineering, data cleaning, ETL pipelines, machine learning, and other production analytics)
  • Proficiency in software engineering fundamentals to include algorithms, data structures, design patterns, and at least one systems programming language (e.g., Go, Rust, C++, Java, Scala, etc.)
  • Proficiency in Python and exposure to libraries like TensorFlow, PyTorch, and/or scikit-learn
  • Exposure to modern software engineering tools and processes (Agile, version control, issue tracking, CI/CD, debugging, etc.)
  • Active Secret (or above) US security clearance
  • Due to the nature of this role, candidates must have US citizenship
The Wish List
We're very interested in candidates who possess the above qualifications, and we appreciate and consider the addition of:
  • Advanced degree in data science, machine learning, computer science, or a related discipline
  • Excellence in Python and deep knowledge of libraries like TensorFlow, PyTorch, and/or scikit-learn
  • Knowledge of relevant architectures and design patterns for client-server systems (e.g., asynchronous programming, REST, GraphQL, React, Vue, Angular)
  • Experience implementing and deploying software into containerized or cloud environments (e.g., Docker, Kubernetes, infrastructure as code, major cloud architectures)
  • Experience with machine learning applied to imagery and/or video data
  • Experience building agentic systems, agentic workflows, or AI agents
  • Experience defining, scoping, planning, and delivering complex technical solutions
  • Experience delivering technology solutions in secure government environments

The anticipated base pay range for this position is $140,000-$165,000/year. Striveworks' total compensation package includes a competitive base salary, equity grants, and cash bonuses.
The Benefits
  • 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

Check us out on Built In!
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 Operations at hr@striveworks.us.
In compliance with federal law, all persons hired will be required to verify 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.