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Machine Learning Engineer Opt Jobs in Austin, TX

webAI Inc

Staff Machine Learning Engineer

Austin, TX · On-site +1

We are seeking an experienced Staff Machine Learning Engineer with a strong background in Large Language Models (LLMs) and/or Mixture of Experts (MoEs). The ideal candidate will have a proven track ...

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 ...

Roku

Senior Machine Learning Engineer

Austin, TX

$121K - $160K/yr

We're looking for seasoned engineers with a background in machine learning to aid in this mission. Examples of problems include improving ad relevance, inferring demographics, yield optimization, and ...

ForeFlight

Staff Machine Learning Engineer

Austin, TX · On-site +1

$208K - $255K/yr

Jeppesen ForeFlight is seeking a Senior Machine Learning Engineer to help build and scale domain-specialized automatic speech recognition (ASR) systems for aviation and operational audio workflows.

Striveworks

Staff Machine Learning Engineer

Austin, TX · On-site +1

The Role As a Staff Machine Learning Engineer at Striveworks, you will be challenged-and trusted-on day one to be both a core contributor and a customer-facing technical leader on the projects and ...

Lauretta AI LLC

Machine Learning Engineer L-1

Austin, TX · On-site

$80K - $93K/yr

* Develop high-quality, maintainable code to build and deploy computer vision modules and machine learning models as part of an AI pipeline * Works with data and software engineering team to integrate ...

Lauretta AI LLC

Machine Learning Engineer L-1

Austin, TX · On-site

$80K - $93K/yr

* Develop high-quality, maintainable code to build and deploy computer vision modules and machine learning models as part of an AI pipeline * Works with data and software engineering team to integrate ...

Lauretta AI LLC

Machine Learning Engineer L-1

Austin, TX · On-site

$80K - $93K/yr

* Develop high-quality, maintainable code to build and deploy computer vision modules and machine learning models as part of an AI pipeline * Works with data and software engineering team to integrate ...

Bumble Inc.

Staff Machine Learning Engineer

Austin, TX · On-site

$300K - $345K/yr

As a Staff Machine Learning Engineer, you'll operate as a highly autonomous technical leader ... If you'd prefer to opt out, simply let your recruiter or interviewer know at the start of a call ...

Realtor.com Careers

Sr. Machine Learning Engineer

Austin, TX · On-site

$103K - $142K/yr

As a Senior Machine Learning Engineer, you'll take a leading technical role in building the consumer-facing products and backend services that bring these ML capabilities to millions of users. You'll ...

Avride

Senior / Staff Machine Learning Engineer

Austin, TX · On-site

$124K - $171K/yr

They are seeking experienced Machine Learning Engineers to drive the development and deployment of machine learning solutions for complex autonomy challenges, including model optimization and ...

Bumble Inc.

Staff Machine Learning Engineer

Austin, TX · On-site

$300K - $345K/yr

As a Staff Machine Learning Engineer, you'll operate as a highly autonomous technical leader ... If you'd prefer to opt out, simply let your recruiter or interviewer know at the start of a call ...

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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 13, 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:
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Machine Learning Engineer Opt jobs near you

Staff Machine Learning Engineer

webAI Inc

Austin, TX • On-site, Remote

Full-time

Medical, Dental, Vision, Retirement

Posted 24 days ago

Job description

About Us:
webAI is the first end-to-end private AI platform. Enterprises and Governments use webAI to bring AI to their data, powering specialized intelligence trained on their own knowledge and compounding in value with every use.
Our approach is guided by a simple philosophy: AI should be specialized, sovereign, efficient, and sustainable. It should solve real problems, not just burn more compute. Our technology enables the development of powerful AI using limited amounts of data, challenging the underlying assumption that big data is the key to unlocking the full power of AI. We are offering a superior career opportunity to join a dynamic and fast-growing team that fosters an exciting and growth-oriented work culture; an opportunity where you can truly put your name on meaningful change for an entire civilization.
About the Role:
We are seeking an experienced Staff Machine Learning Engineer with a strong background in Large Language Models (LLMs) and/or Mixture of Experts (MoEs). The ideal candidate will have a proven track record of developing and deploying advanced AI models. You will lead core product initiatives across on-device inference optimization, quantization, RAG, agentic framework and/or tool calling. You will also be responsible for end-to-end delivery working cross functionally with other engineering functions and lead the sub-team.
Responsibilities:
  • Lead the development and optimization of Large Language Models and Mixture of Experts models.
  • Collaborate with cross-functional teams to integrate ML models into our platform.
  • Conduct cutting-edge research in machine learning, with a focus on improving the performance and efficiency of LLMs.
  • Stay abreast of the latest advancements in AI and ML, and apply this knowledge to improve our models and methodologies.
  • Mentor junior engineers and contribute to the team's knowledge sharing and best practices.

Qualifications:
  • Advanced degree (Ph.D. preferred) in Computer Science, or a related field.
  • Proven track record of building and innovations through publications or industry experience.
  • Minimum of 6 years of experience in machine learning, with specific expertise in Large Language Models and Mixture of Experts.
  • Strong programming skills in Python and machine learning frameworks like TensorFlow and/or PyTorch.
  • Demonstrated ability to lead complex projects and work collaboratively in a team environment.
  • Excellent problem-solving skills and a passion for innovation.

Preferred Skills:
  • Experience with cloud computing services (AWS, Azure, GCP).
  • Knowledge of Big Data technologies (Hadoop, Spark).
  • Familiarity with containerization and orchestration technologies (Docker, Kubernetes).
  • Publications or presentations in recognized Machine Learning journals or conferences.

We at webAI are committed to living out the core values we have put in place as the foundation on which we operate as a team. We seek individuals who exemplify the following:
  • Truth - Emphasizing transparency and honesty in every interaction and decision.
  • Ownership - Taking full responsibility for one's actions and decisions, demonstrating commitment to the success of our clients.
  • Tenacity - Persisting in the face of challenges and setbacks, continually striving for excellence and improvement.
  • Humility - Maintaining a respectful and learning-oriented mindset, acknowledging the strengths and contributions of others.

Benefits:
We strive to provide competitive benefits to all employees. The benefits listed in this posting generally apply to U.S.-based employees. For employees hired outside the United States, benefits may vary based on local law, country-specific requirements, and the employment platform or entity through which the employee is hired.
  • Competitive salary
  • Comprehensive health, dental, and vision benefits package
  • 401(k) match
  • Equity options
  • $200/month Health & Wellness stipend
  • Continuing Education support
  • $500/year Function Health subscription
  • Free parking for in-office employees
  • Flexible Time Off (FTO)
  • Parental leave for eligible employees
  • Supplemental life insurance

webAI is an Equal Opportunity Employer and does not discriminate against any employee or applicant on the basis of age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances. We adhere to these principles in all aspects of employment, including recruitment, hiring, training, compensation, promotion, benefits, social and recreational programs, and discipline. In addition, it is the policy of webAI to provide reasonable accommodation to qualified employees who have protected disabilities to the extent required by applicable laws, regulations and ordinances where a particular employee works.

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