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Mobile Machine Learning Jobs in Texas (NOW HIRING)

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 ... Badoo, which was founded in 2006, is one of the pioneers of web and mobile dating products. AI ...

Bumble Inc.

Staff Machine Learning Engineer

Austin, TX

$300K - $345K/yr

As part of the Machine Learning team, you'll play a critical role in shaping how AI powers ... Badoo, which was founded in 2006, is one of the pioneers of web and mobile dating products. AI ...

Bumble Inc.

Staff Machine Learning Engineer

Austin, TX · On-site

$300K - $345K/yr

As part of the Machine Learning team, you'll play a critical role in shaping how AI powers ... Badoo, which was founded in 2006, is one of the pioneers of web and mobile dating products. AI ...

Bumble Inc.

Lead Machine Learning Engineer

Austin, TX · On-site

$255K - $280K/yr

As a Lead Machine Learning Engineer, you'll take ownership of complex, ambiguous problem spaces and ... Badoo, which was founded in 2006, is one of the pioneers of web and mobile dating products. AI ...

Bumble Inc.

Lead Machine Learning Engineer

Austin, TX

$255K - $280K/yr

As a Lead Machine Learning Engineer, you'll take ownership of complex, ambiguous problem spaces and ... Badoo, which was founded in 2006, is one of the pioneers of web and mobile dating products. AI ...

webAI Inc

Senior Machine Learning Engineer

Austin, TX · On-site

$103.60K - $142.20K/yr

We are seeking a Senior Machine Learning Engineer to support our Public Sector initiatives focused ... Proven experience deploying AI models across cloud, edge, and mobile hardware environments.

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How much do mobile machine learning jobs pay per hour?

As of May 30, 2026, the average hourly pay for mobile machine learning in Texas is $23.59, according to ZipRecruiter salary data. Most workers in this role earn between $13.41 and $18.80 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Mobile Machine Learning Engineer, and why are they important?

To thrive as a Mobile Machine Learning Engineer, you need a solid background in computer science, machine learning, and mobile application development, often supported by a relevant degree and experience. Proficiency with ML frameworks (like TensorFlow Lite or Core ML), mobile platforms (Android/iOS), and deployment tools is typically required. Strong problem-solving skills, adaptability, and effective communication set standout professionals apart in this field. These skills are crucial for successfully developing, optimizing, and integrating machine learning models into efficient and user-friendly mobile applications.

What are some common challenges faced by Mobile Machine Learning engineers when deploying models on mobile devices?

Mobile Machine Learning engineers often encounter challenges related to limited computational resources and memory constraints on mobile devices. Optimizing models for efficient inference without significant loss in accuracy is a key hurdle, as is ensuring compatibility across different devices and operating systems. Additionally, balancing power consumption and real-time performance is critical, so engineers frequently collaborate with mobile app developers and hardware specialists to deliver seamless user experiences while maintaining model integrity.

What is mobile machine learning?

Mobile machine learning refers to the development and deployment of machine learning models on mobile devices such as smartphones and tablets. It enables apps to perform tasks like image recognition, language translation, and speech processing directly on the device without needing to send data to the cloud. This approach improves privacy, reduces latency, and can work even without an internet connection. Developers use frameworks like TensorFlow Lite, Core ML, and PyTorch Mobile to optimize models for the limited resources of mobile hardware.

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

AspectMobile Machine LearningData Scientist
Required CredentialsBachelor's in CS, ML, or related; experience with mobile platformsBachelor's or higher in CS, Statistics, or related; data analysis skills
Work EnvironmentMobile app development teams, on-device processingData analysis teams, research environments
Industry UsageMobile app companies, tech startupsFinance, healthcare, tech firms
Common Search/ComparisonYesYes

Mobile Machine Learning focuses on developing ML models optimized for mobile devices and integrating them into mobile apps. Data Scientists analyze large datasets to extract insights and build predictive models across various industries. While both roles require programming and ML knowledge, Mobile Machine Learning emphasizes on-device deployment and mobile platform expertise, whereas Data Scientists focus on data analysis and model development for broader applications.

What are the most commonly searched types of Machine Learning jobs in Texas? The most popular types of Machine Learning jobs in Texas are:
What are popular job titles related to Mobile Machine Learning jobs in Texas? For Mobile Machine Learning jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Mobile Machine Learning jobs in Texas look for? The top searched job categories for Mobile Machine Learning jobs in Texas are:
What cities in Texas are hiring for Mobile Machine Learning jobs? Cities in Texas with the most Mobile Machine Learning job openings:
Mobile Machine Learning jobs near you
Senior Machine Learning Engineer

Senior Machine Learning Engineer

Bumble Inc.

Austin, TX

$220K - $250K/yr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 21 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.
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