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Machine Learning Engineer Opt Jobs in Austin, TX

Senior Machine Learning Engineer

Austin, TX ยท 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 ...

Senior Machine Learning Engineer

Austin, TX ยท 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 ...

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 ...

Senior Machine Learning Engineer

Austin, TX ยท On-site

$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 ...

Staff Machine Learning Engineer

Austin, TX ยท 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.

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 ...

Machine Learning Engineer L-1

Austin, TX ยท 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 ...

Machine Learning Engineer L-1

Austin, TX ยท 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 ...

* 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 ...

Sr. Machine Learning Engineer

Austin, TX

$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 ...

New

Staff Machine Learning Engineer

Austin, TX ยท 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 ...

Senior / Staff Machine Learning Engineer

Austin, TX ยท On-site

$124K - $171K/yr

We are hiring experienced Machine Learning Engineers across Senior, Staff, and Principal levels to drive the development and deployment of machine learning solutions for real-world autonomous systems.

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Showing results 1-20

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 11, 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 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:
Senior Machine Learning Engineer

Senior Machine Learning Engineer

Bumble Inc.

Austin, TX โ€ข On-site

$220K - $250K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 3 days ago


Job description

Introduction to the role & team At Bumble, we're building a world where all relationships are healthy and equitable, and machine learning is central to how we make that real for millions of people every day. As part of our Machine Learning team, you'll help shape intelligent systems that power meaningful connections, safer interactions, and more personalised experiences across our platform.
As a Senior Machine Learning Engineer, you'll own impactful problems end-to-end-from data exploration through to production deployment, while collaborating closely with Product, Engineering, and Data partners. You'll bring curiosity into how we experiment, iterate, and improve, and you'll role model our values of Curiosity and Excellence by continuously raising the bar in how we build and apply AI.
AI is deeply embedded in how we evolve at Bumble. In this role, you'll independently apply modern machine learning and emerging AI techniques, contributing to scalable systems while ensuring thoughtful, responsible use of AI in everything we ship.
What you'll do
  • Build and deploy machine learning models that improve recommendations, ranking, and personalization, driving measurable impact on user experience and engagement
  • Own problems end-to-end, from data exploration and feature engineering through to model training, evaluation, and production deployment
  • Develop and maintain scalable ML pipelines using tools such as Spark and Airflow to support reliable, high-quality model delivery
  • Apply modern ML frameworks (e.g. PyTorch or TensorFlow) to design, train, and optimise models in production environments
  • Contribute to experimentation frameworks, including A/B testing and offline evaluation, to iterate on model performance with an agile mindset
  • Collaborate cross-functionally with Product and Engineering, working with purpose to translate product questions into ML solutions
  • Take ownership of delivering high-quality solutions and see work through from insight to impact, balancing speed and rigor
  • Apply responsible AI practices, ensuring fairness, transparency, and safety are considered in model development and deployment

About You
  • Typically requires 5-8 years of experience, though we welcome candidates with alternative backgrounds that demonstrate equivalent skills.
  • Strong experience building and deploying machine learning models in production environments
  • Proficiency in Python and experience with at least one major ML framework (e.g. PyTorch, TensorFlow)
  • Experience working with data pipelines and distributed systems (e.g. Spark, Airflow) to support ML workflows
  • Familiarity with experimentation methodologies such as A/B testing and model evaluation techniques
  • Ability to collaborate effectively across functions, demonstrating strong ownership and a collaborative mindset
  • Demonstrates an agile mindset, adapting approaches based on data and evolving priorities while maintaining focus on outcomes
  • Growing AI fluency, with the ability to independently apply ML techniques and emerging tools (including LLMs) to solve problems responsibly

$220,000 - $250,000 a year
For base compensation, we set standard ranges for all roles based on function, level, and geographic location. This position is also typically eligible to participate in our short- and long-term incentive programs. Benefits include Medical, Dental, Vision, 401(k) match, Unlimited Paid Time Off Policy.
Maven Fertility: $10,000 lifetime benefit for fertility, adoption, abortion care, and more.
26 Weeks Parental Leave: For both primary and secondary caregivers.
Family & Compassionate Leave: Inclusive of domestic violence recovery.
Unlimited Paid Time Off: Take the time you need.
Company-wide Week Off: Annual collective rest for the entire company.
Focus Fridays: No meetings, emails, or deadlines-just deep work.
About Us
Bumble Inc. is the parent company of Bumble Date, BFF, and Badoo. The Bumble platform enables people to build healthy and equitable relationships, through Kind Connections. Founded by Whitney Wolfe Herd in 2014, Bumble was one of the first dating apps built with women at the center and connects people across dating (Bumble Date) and friendship (BFF). BFF is a friendship app where people in all stages of life can meet people nearby and create meaningful platonic connections and community based on shared interests. Badoo, which was founded in 2006, is one of the pioneers of web and mobile dating products.
AI Fluency
AI is important to us. We're excited by people who are curious and experimental, and who think thoughtfully about how AI can amplify their impact and outcomes.
We encourage you to use AI responsibly as you prepare your application. Please don't use it to fabricate experiences or answer questions live in interviews. We care deeply about authenticity and want to understand your real skills, judgment and voice, because building a meaningful, genuine connection with you matters to us.
Final Compensation
Will be determined based on factors such as the selected candidate's qualifications, relevant experience, skill set, and other job-related considerations.
Benefits & Perks
Insurance: Medical/dental/vision, 30-day eligibility. Bumble has multiple competitive offerings that will be available to you on the first of the month following date of hire.
Unlimited PTO + 1 company-wide week off + Focus Fridays every week
Fully paid life and long-term disability insurance
401k with 4% company match if you contribute 6%, 90-day eligibility
Monthly wellness benefit and access to Noom, Unmind, and Your Money Line
Maternity and Fertility benefit + 26 week paid parental leave
Premium App Access
Inclusion at Bumble Inc.
Bumble Inc. is an equal opportunity employer and we strongly encourage people of all ages, colour, lesbian, gay, bisexual, transgender, queer and non-binary people, veterans, parents, people with disabilities, and neurodivergent people to apply. We're happy to make any reasonable adjustments that will help you feel more confident throughout the process, please don't hesitate to let us know how we can help.
In your application, please feel free to note which pronouns you use (For example: she/her, he/him, they/them, etc).
AI in Bumble Inc. Hiring
At Bumble, we may use AI tools to support parts of our recruitment process - such as helping us record, transcribe, and summarize conversations, and supporting job alignment by comparing resumes and job descriptions to highlight skills and potential roles that may be a good match. These tools help us work more efficiently and stay focused on you during our conversations. Importantly, all hiring decisions are made by people. AI is used only to support our team's efficiency and improve the candidate experience - not to evaluate or decide on your candidacy. Participation in AI-supported interviews and conversations is completely voluntary and will not impact your candidacy. If you'd prefer to opt out, simply let your recruiter or interviewer know at the start of a call, or anytime during the interview or conversation. Summaries and related data are retained only as long as needed in line with our internal data retention policies. If at any point you'd like a transcription or summary deleted, please contact your recruiter directly.
For further information on how we hold and manage your data, please refer to our Privacy Policy.