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

CesiumAstro

Senior Machine Learning Engineer II

Austin, TX · On-site

$103K - $142K/yr

We are looking for a Senior Machine Learning Engineer II to contribute to the development and ... Document designs, workflows, and operational best practices to ensure maintainable and resilient ML ...

CesiumAstro

Senior Machine Learning Engineer II

Austin, TX · On-site

$103K - $142K/yr

We are looking for a Senior Machine Learning Engineer II to contribute to the development and ... Document designs, workflows, and operational best practices to ensure maintainable and resilient ML ...

CesiumAstro

Senior Machine Learning Engineer II

Austin, TX · On-site

$103K - $142K/yr

We are looking for a Senior Machine Learning Engineer II to contribute to the development and ... Document designs, workflows, and operational best practices to ensure maintainable and resilient ML ...

Deloitte

Lead Generative AI Data Engineer III

Austin, TX · On-site

$101K - $133K/yr

... machine learning operations processes. The wage range for this role takes into account a wide range of factors considered in making compensation decisions, including but not limited to skill sets ...

Deloitte

Lead Generative AI Data Engineer III

Austin, TX · On-site

$101K - $133K/yr

... machine learning operations processes. The wage range for this role takes into account a wide range of factors considered in making compensation decisions, including but not limited to skill sets ...

Apple

Data Engineer

Austin, TX · On-site

$113K - $136K/yr

... machine learning operations (MLOps) practices Experience with data visualization tools and business intelligence platforms

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All JobsMachine Learning Operations JobsMachine Learning Operations Jobs in Austin, TX

Machine Learning Operations information

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$21

$39

$60

How much do machine learning operations jobs pay per hour?

As of Sep 2, 2026, the average hourly pay for machine learning operations in Austin, TX is $39.54, according to ZipRecruiter salary data. Most workers in this role earn between $33.12 and $41.92 per hour, depending on experience, location, and employer.

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

AspectMachine Learning OperationsData Scientist
Primary FocusDeploying, maintaining, and scaling ML models in productionAnalyzing data to develop insights and build models
Required SkillsML deployment, cloud platforms, automation, scriptingStatistical analysis, data visualization, programming (Python/R)
Work EnvironmentOperations teams, cloud infrastructure, production systemsResearch environments, data analysis teams, R&D
Common CertificationsCloud certifications, MLOps tools certificationsData science certifications, statistical courses

Machine Learning Operations and Data Scientists often collaborate, but MLOps focuses on deploying and maintaining models in production, while Data Scientists focus on analyzing data and developing models. Both roles require technical skills, but their day-to-day tasks and environments differ.

Is machine learning operations a high paying job?

Machine Learning Operations (MLOps) roles typically offer high salaries due to the specialized skills required, such as expertise in cloud platforms, automation, and data engineering. Compensation varies based on experience, location, and company size, but generally ranks among well-paying tech jobs.

What are machine learning operations?

Machine Learning Operations (MLOps) is a set of practices that combines machine learning, software engineering, and DevOps to deploy, monitor, and maintain machine learning models in production environments. It involves tasks such as model versioning, automation, testing, and ensuring scalability and reliability using tools like CI/CD pipelines and cloud platforms.

What cities near Austin, TX are hiring for Machine Learning Operations jobs?

Cities near Austin, TX with the most Machine Learning Operations job openings:

Machine Learning Operations jobs near you
Infographic showing various Machine Learning Operations job openings in Austin, TX as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 15% Part Time, 1% Temporary, and 2% Contract. Highlights an 94% Physical, 2% Hybrid, and 4% Remote job distribution, with an average salary of $82,244 per year, or $39.5 per hour.

Finance Machine Learning Engineer - Tech Lead

Apple

Austin, TX

$101K - $133K/yr

Full-time

Re-posted 13 days ago

Apple rating

8.1

Company rating: 8.1 out of 10

Based on 680 frontline employees who took The Breakroom Quiz

6th of 30 rated technology retailers

Job description

Imagine what you could do here. At Apple, new ideas have a way of becoming great products, services, and customer experiences very quickly. Bring passion and curiosity to your job and there's no telling what you could accomplish. Do you love thinking analytically? Just as our customers find value in Apple products, the Finance group finds value for both Apple and its shareholders. As a machine learning engineer in Finance, you’ll play an integral role in building the data foundations, services, and platforms used for delivering insights and automating decisions for Apple’s Finance organization.
Description
This role will be the technical lead for product cost, supporting our Operations Finance organization. You will work as part of a multi-discipline engineering pod with data and software engineers, product managers and program managers. Your ability to learn business processes and instill strong engineering practices into team machine learning processes will be critical. A key part of your role will be to operationalize AI solutions, bridging the gap between prototype and production to rapidly and reliably deliver value to the Finance organization.","responsibilities":"Technical lead overseeing solution design and engineers
Partner with teammates and share expertise across teams
Explain technical concepts to non-technical audiences
Collaborate effectively with cross-functional teams
Operationalize AI solutions, bridging the gap between prototype and production
Instill strong engineering practices into team machine learning processes
Rapidly and reliably deliver value to the Finance organization
Preferred Qualifications
Previous experience working in a corporate finance, accounting, or supply chain organization
Understanding of or ability to learn financial statements, P&L impact, high level accounting principles, SOX and tax compliance and month-end close process
Minimum Qualifications
At least 8 years experience in an engineering role
At least one year experience effectively leading engineers and collaborating cross-functionally, translating technical concepts for diverse audiences and converting ideas into solutions with strong process and data understanding
Experience building data models and scalable pipelines using SQL and big data technologies, with expertise in data ops best practices
Experience developing in Python while following and advocating for DRY principles, modularity, testing standards, version control, and code reviews. Experience with front end (.js experience)
Experience applying ML algorithms for regression, classification, and anomaly detection; build generative AI and agentic solutions; implement MLOps/LLMOps including CI/CD, drift monitoring, and familiarity working with cloud platforms (AWS, GCP, Azure)
Graduate degree (computer science, data science, math, quantitative finance, or similar discipline)
Undergraduate degree (computer science, data science, finance, economics, accounting, or related business discipline)

What Apple employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Apple logo

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

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