1

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

We are hiring Senior Machine Learning Engineers We are hiring engineers with significant expertise in both machine learning and software engineering. You will be working with our engineering and ...

New

We are looking for visionary Machine Learning Engineers to join our Applied Group, where you'll transform groundbreaking research into real-world applications that can change industries, enhance ...

We are hiring Senior Machine Learning Engineers We are hiring engineers with significant expertise in both machine learning and software engineering. You will be working with our engineering and ...

Senior Machine Learning Engineer

Austin, TX · On-site +1

$335K - $400K/yr

We are hiring Senior Machine Learning Engineers We are hiring engineers with significant expertise in both machine learning and software engineering. You will be working with our engineering and ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

As an AI Engineering team member, you will be instrumental in advancing new features and/or solutions from the Proof of Concept stage to full production readiness. Your role involves refining and ...

Senior Machine Learning Engineer

Austin, TX · On-site

$121K - $160K/yr

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 ...

Senior Machine Learning Engineer

Austin, TX · On-site

$121K - $160K/yr

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 ...

We are looking for a Machine Learning Engineer to help us design and deliver CX solutions that provide our clients with a beautiful customer journey that achieves results. At PTP we value aptitude ...

Showing results 21-40

Machine Learning Engineer information

See Austin, TX salary details

$31.2K

$127.6K

$191.8K

How much do machine learning engineer jobs pay per year?

As of Aug 19, 2026, the average yearly pay for machine learning engineer in Austin, TX is $127,637.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,600.00 and $153,600.00 per year, depending on experience, location, and employer.

What is a machine learning engineer?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

What does a machine learning engineer do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

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

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

What are some common challenges faced by machine learning engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

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

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

What are the most commonly searched types of Machine Learning Engineer jobs in Austin, TX?

The most popular types of Machine Learning Engineer jobs in Austin, TX are:

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

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

Infographic showing various Machine Learning Engineer job openings in Austin, TX as of August 2026, with employment types broken down into 100% Full Time. Highlights an 80% In-person, and 20% Remote job distribution, with an average salary of $127,637 per year, or $61.4 per hour.

Machine Learning Engineer - People Analytics

Apple

Austin, TX

$184K - $277K/yr

Full-time

Medical, Dental, Retirement

Re-posted 6 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

At Apple, our greatest resource is our people, and the People Analytics Team is dedicated to ensuring Apple’s employees are able to do the best work of their lives.
Our team is looking for a Machine Learning Engineer who is passionate about crafting, implementing, and operating analytical and machine learning solutions that have direct and measurable impact to Apple and its employees.
As a Machine Learning Engineer on Apple's People Analytics Team, you will employ predictive modeling, statistical analysis, and advanced analytical techniques to support solutions for talent management, employee surveys, compensation, and recruiting.
Apple's dedication to privacy, the human-centric nature of our work, and the scale of our business present exciting challenges to traditional machine learning and data science methods. On this team, you will push the limits of existing approaches while delivering tangible business value.
Description
As a Machine Learning Engineer on our team will engage with our business partners to understand their problems, design data-driven solutions, and produce proof-of-concept and prototype solutions. They will collaborate with data engineers and system architects to implement these solutions in a production environment, and be responsible for the ongoing analytic operation of these solution.
","responsibilities":"Design data science / machine learning approaches, applying tried-and-true techniques or developing custom algorithms as needed by the business problem.
Collaborate with data engineers and platform architects to implement real-time and batch decisioning solutions in production.
Ensure operational and business metric health by monitoring production decision points.
Develop metrics to measure performance of analytics solutions, and regularly communicate results to business partners and executives.
Research new technologies and methods across machine learning, data engineering, and data visualization to improve the technical capabilities of the team.
Preferred Qualifications
Ph.D. in I-O Psychology, Economics, Operations Research, Computer Science, or Statistics with a data science fellowship or prior professional experience as a data scientist
Experience working with employee data or HR systems
Minimum Qualifications
MS with 5+ years of professional experience applying data science to real-world business problems
Practical experience with and theoretical understanding of algorithms for classification, regression, clustering, and anomaly detection
Proficiency in writing SQL queries involving database joins and analytical/window functions
Ability to implement data science pipelines, analyses, and applications in a programming language such as Python or R
Prior experience working with employee data or HR systems
Experience with natural language processing (sentiment, topic identification, summarization, entity extraction) and network analysis a plus.
Ability to translate business processes and data into an analytic solution.
Ability to comprehend and debug complex systems integrations spanning multiple toolchains and teams
Ability to extract meaningful business insights from data and identify the stories behind the patterns
Excellent presentation skills, distilling complex analysis and concepts into concise business-focused takeaways
Creativity to engineer novel features and signals, and to push beyond current tools and approaches
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 $277,600, 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

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