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

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 ...

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 · 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 ...

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 ...

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.

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 ...

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 ...

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 ...

As a Staff Machine Learning Engineer, you'll operate as a highly autonomous technical leader, owning large, complex problem spaces and driving end-to-end machine learning systems that influence ...

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, owning large, complex problem spaces and driving end-to-end machine learning systems that influence ...

Senior / Staff Machine Learning Engineer

Austin, TX · 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.

Senior Machine Learning Engineer II

Austin, TX · On-site

$103K - $142K/yr

They are seeking a Senior Machine Learning Engineer II to contribute to the development and deployment of machine learning solutions for advanced distributed processing platforms, working ...

Senior Machine Learning Engineer

Austin, TX · 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 ...

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Machine Learning Engineer information

See Austin, TX salary details

$31.3K

$128.1K

$192.5K

How much do machine learning engineer jobs pay per year?

As of Jul 9, 2026, the average yearly pay for machine learning engineer in Austin, TX is $128,111.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,000.00 and $154,200.00 per year, depending on experience, location, and employer.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-demand industries or companies can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially in tech giants or startups with significant funding.

What do machine learning engineers do?

Machine learning engineers develop algorithms and models that enable computers to learn from data and make predictions or decisions. They often work with large datasets, use programming languages like Python or Java, and utilize tools such as TensorFlow or PyTorch to build, test, and deploy machine learning systems in production environments.

What are Machine Learning Engineers?

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 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.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as AI advances, as they develop and refine algorithms, models, and systems. Roles that require complex problem-solving, creativity, and domain expertise—such as healthcare professionals, data scientists, software developers, cybersecurity specialists, and AI ethics officers—are also expected to persist due to their reliance on human judgment and specialized knowledge. These jobs often involve skills that are difficult for AI to fully replicate or replace.

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 engineers make $300,000 a year?

Senior machine learning engineers and data scientists with extensive experience, advanced skills in deep learning, and proficiency with tools like TensorFlow or PyTorch can earn $300,000 or more annually, especially in high-cost-of-living areas or top tech companies. Compensation often includes base salary, bonuses, and stock options, reflecting their expertise and impact on business outcomes.

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:
Senior Machine Learning Engineer

Senior Machine Learning Engineer

Bumble Inc.

Austin, TX

$220K - $250K/yr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted yesterday


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.
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