ZipRecruiter

Log In

1

Machine Learning Engineer Opt Jobs in Austin, TX

Q2

Machine Learning Engineer

Austin, TX · Hybrid

Summary The Machine Learning Engineer designs and evolves enterprise AI systems and architectures that enable scalable, secure, and high-impact adoption across the organization. This role defines end ...

Q2 Software, Inc.

Machine Learning Engineer

Austin, TX · On-site

Summary The Machine Learning Engineer designs and evolves enterprise AI systems and architectures that enable scalable, secure, and high-impact adoption across the organization. This role defines end ...

9 Mothers

Machine Learning Engineer, Senior

Austin, TX · On-site

$103K - $142K/yr

The company is seeking a Senior Machine Learning Engineer to design, train, and maintain models for their counter-sUAS perception stack, focusing on model research and dataset engineering.

Bespoke Labs

Machine Learning Engineer

Austin, TX · On-site

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 ...

Iterable

Senior Machine Learning Engineer (Nova)

Austin, TX · On-site

$103K - $142K/yr

They are seeking a Senior Machine Learning Engineer to build core Machine Learning foundations, focusing on applied Machine Learning in production environments, and collaborating with various teams ...

Apple

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 ...

Striveworks

Senior Machine Learning Engineer

Austin, TX · On-site +1

$121K - $160K/yr

The Role As a Senior 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 ...

PTP

Machine Learning Engineer - REMOTE

Austin, TX · On-site +1

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 ...

Apple

Senior Machine Learning Engineer

Austin, TX

$184K - $324K/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 ...

Apple

Senior Machine Learning Engineer

Austin, TX

$184K - $324K/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 ...

Apple

Senior Machine Learning Engineer

Austin, TX

$184K - $324K/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 ...

Bumble Inc.

Senior Machine Learning Engineer

Austin, TX · On-site

$220K - $250K/yr

As a Senior Machine Learning Engineer, you'll own impactful problems end-to-end-from data ... If you'd prefer to opt out, simply let your recruiter or interviewer know at the start of a call ...

next page

Showing results 1-20

All JobsMachine Learning Engineer Opt JobsMachine Learning Engineer Opt Jobs in Austin, TX

Machine Learning Engineer Opt information

See Austin, TX salary details

$31.2K

$127.6K

$191.8K

How much do machine learning engineer opt jobs pay per year?

As of Jul 9, 2026, the average yearly pay for machine learning engineer opt 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 are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models into production environments. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, reliable systems that organizations can use to make predictions or automate tasks. Their responsibilities include data preprocessing, choosing appropriate algorithms, model training, and ensuring the model's performance in real-world applications. Machine Learning Engineers often collaborate with data scientists, data engineers, and product teams to deliver intelligent solutions.

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

AspectMachine Learning Engineer OptData Scientist
Required CredentialsBachelor's or Master's in CS, AI, or related fields; certifications in ML toolsBachelor's or Master's in CS, Statistics, or related fields; data analysis certifications
Work EnvironmentDevelops, tests, and deploys ML models in production systemsAnalyzes data, builds models, and provides insights for decision-making
Employer & Industry UsageTech companies, AI startups, e-commerce, financeResearch institutions, tech firms, consulting, finance
Common Search & ComparisonOften compared for technical skills and deployment focusCompared for data analysis and business insights

Machine Learning Engineers Opt focus on deploying scalable ML models in production environments, while Data Scientists primarily analyze data and develop models for insights. Both roles require strong technical skills, but their core responsibilities differ in application and deployment.

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 a solid background in mathematics, statistics, and programming (especially Python), typically supported by a degree in computer science, engineering, or a related field. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch), data processing tools, and cloud platforms, along with relevant certifications, is highly valuable. Strong problem-solving ability, collaboration, and effective communication are standout soft skills in this role. These skills and qualities ensure the successful development, deployment, and integration of machine learning solutions that drive business value.

What are some common challenges Machine Learning Engineers face when deploying models to production environments?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, handling data drift, and integrating models seamlessly with existing systems when deploying to production. Monitoring model performance in real time and retraining models as new data becomes available are also critical tasks. Collaboration with data engineers and DevOps teams is essential to address infrastructure and deployment hurdles while maintaining model accuracy and reliability.
What are popular job titles related to Machine Learning Engineer Opt jobs in Austin, TX? For Machine Learning Engineer Opt jobs in Austin, TX, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Opt jobs in Austin, TX look for? The top searched job categories for Machine Learning Engineer Opt jobs in Austin, TX are:
What cities near Austin, TX are hiring for Machine Learning Engineer Opt jobs? Cities near Austin, TX with the most Machine Learning Engineer Opt job openings:
Machine Learning Engineer Opt jobs near you

Staff Machine Learning Engineer

TalentPros.AI

Austin, TX

$120K - $550K/yr

Full-time

Posted 15 days ago

Job description

About the Team

We are at the forefront of artificial intelligence, driving innovation and shaping the future with cutting-edge research. Our mission is to ensure that AI's benefits reach everyone. 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 human creativity, and solve complex problems.


About the Role

As a Machine Learning Engineer in our Applied Group, you will have the opportunity to work with some of the brightest minds in AI. You'll contribute to deploying state-of-the-art models in production environments, helping turn research breakthroughs into tangible solutions. If you're excited about making AI technology accessible and impactful, this role is your chance to make a significant mark.

In this role, you will:

  • Innovate and Deploy: Design and deploy advanced machine learning models that solve real-world problems. Bring our research from concept to implementation, creating AI-driven applications with a direct impact.
  • Collaborate with the Best: Work closely with researchers, software engineers, and product managers to understand complex business challenges and deliver AI-powered solutions. Be part of a dynamic team where ideas flow freely and creativity thrives.
  • Optimize and Scale: Implement scalable data pipelines, optimize models for performance and accuracy, and ensure they are production-ready. Contribute to projects that require cutting-edge technology and innovative approaches.
  • Learn and Lead: Stay ahead of the curve by engaging with the latest developments in machine learning and AI. Take part in code reviews, share knowledge, and lead by example to maintain high-quality engineering practices.
  • Make a Difference: Monitor and maintain deployed models to ensure they continue delivering value. Your work will directly influence how AI benefits individuals, businesses, and society at large.


You might thrive in this role if you:

  • Master's/ PhD degree in Computer Science, Machine Learning, Data Science, or a related field. 
  • Demonstrated experience in deep learning and transformers models
  • Proficiency in frameworks like PyTorch or Tensorflow
  • Strong foundation in data structures, algorithms, and software engineering principles.
  • Experience with search relevance, ads ranking or LLMs is a plus.
  • Are familiar with methods of training and fine-tuning large language models, such as distillation, supervised fine-tuning, and policy optimization
  • Excellent problem-solving and analytical skills, with a proactive approach to challenges.
  • Ability to work collaboratively with cross-functional teams.
  • Ability to move fast in an environment where things are sometimes loosely defined and may have competing priorities or deadlines
  • Enjoy owning the problems end-to-end, and are willing to pick up whatever knowledge you're missing to get the job done


We are an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity.