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

Senior Fullstack/Frontend Engineer

Austin, TX · On-site

$144.70 - $261.30/hr

... machine learning workflows related to map labeling or perception. * Deep experience with Node.js internals and performance tuning. * Experience designing performant geospatial services, coordinate ...

... construction, geospatial, government, transportation, and more. AECO: Trimble is empowering ... Our impact is tangible, from connected machines that save fuel to data-driven insights that reduce ...

Showing results 21-27

Machine Learning Geospatial information

See Austin, TX salary details

$18

$28

$46

How much do machine learning geospatial jobs pay per hour?

As of Aug 16, 2026, the average hourly pay for machine learning geospatial in Austin, TX is $28.89, according to ZipRecruiter salary data. Most workers in this role earn between $22.40 and $33.61 per hour, depending on experience, location, and employer.

What does a Machine Learning Geospatial professional do?

A Machine Learning Geospatial professional uses machine learning techniques to analyze and interpret geospatial data, such as satellite imagery, maps, and GPS data. Their work involves building and training models to detect patterns, make predictions, and solve spatial problems in fields like agriculture, urban planning, disaster response, and environmental monitoring. These professionals often collaborate with data scientists and GIS (Geographic Information Systems) specialists to extract actionable insights from large and complex geospatial datasets. Their skills are crucial for automating tasks such as image classification, land cover mapping, and object detection in geographic contexts.

What are some common challenges faced by Machine Learning Geospatial professionals when integrating spatial data into predictive models?

Machine Learning Geospatial professionals often encounter challenges such as managing large and complex spatial datasets, ensuring data quality and consistency, and handling spatial autocorrelation that can bias model results. Additionally, integrating diverse data sources—like satellite imagery, sensor data, and GIS layers—requires advanced pre-processing and domain knowledge. Collaborating with GIS analysts and domain experts is usually essential to develop robust models that provide actionable insights.

What is the difference between Machine Learning Geospatial vs GIS Analyst?

AspectMachine Learning GeospatialGIS Analyst
Required CredentialsBachelor's or higher in Computer Science, Data Science, or related fields; knowledge of machine learning and geospatial dataBachelor's in Geography, GIS, or related fields; proficiency in GIS software
Work EnvironmentTech companies, data science teams, research institutionsGovernment agencies, urban planning, environmental firms
Industry UsageData-driven geospatial analysis, predictive modeling, AI applicationsMapping, spatial data management, spatial analysis

Machine Learning Geospatial professionals focus on applying machine learning techniques to analyze geospatial data, often working with large datasets and developing predictive models. GIS Analysts primarily handle spatial data management, mapping, and analysis using GIS software. While both roles work with geospatial data, Machine Learning Geospatial roles emphasize data science and AI, whereas GIS Analysts focus on spatial information management and visualization.

What are the key skills and qualifications needed to thrive as a Machine Learning Geospatial professional?

To thrive as a Machine Learning Geospatial specialist, you need a strong background in machine learning, geospatial analysis, programming (Python, R), and a relevant degree in computer science, geography, or a related field. Familiarity with GIS software (e.g., ArcGIS, QGIS), remote sensing tools, and cloud platforms like Google Earth Engine or AWS is typically required. Analytical thinking, problem-solving, and effective communication are vital soft skills for interpreting data and collaborating with multidisciplinary teams. These skills and qualities are crucial for developing accurate geospatial models and delivering actionable insights from complex spatial data.

What are popular job titles related to Machine Learning Geospatial jobs in Austin, TX?

For Machine Learning Geospatial jobs in Austin, TX, the most frequently searched job titles are:

What job categories do people searching Machine Learning Geospatial jobs in Austin, TX look for?

The top searched job categories for Machine Learning Geospatial jobs in Austin, TX are:

What cities near Austin, TX are hiring for Machine Learning Geospatial jobs?

Cities near Austin, TX with the most Machine Learning Geospatial job openings:

Staff Software Engineer - (Matching and Recommendations)

Bumble Inc.

Austin, TX • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 19 days ago


Job description

At Bumble, we're building a world where all relationships are healthy and equitable, and machine learning is central to making that a reality for millions of people every day. As part of our Machine Learning team in Recommendations, you'll help shape intelligent systems that power meaningful connections, safer interactions, and more personalized experiences across our platform.
Join our team at Bumble, where we're revolutionizing online dating through innovative AI-driven experiences. We're seeking machine learning engineers to spearhead the development of the next generation of online dating. In this role, you will be a foundational member of a small, dynamic team dedicated to creating cutting-edge solutions that redefine how people connect and form relationships online.
The ideal candidate thrives in a fast-paced environment, is a creative thinker, and has a proven track record in Generative AI and Machine Learning. If you're passionate about leveraging AI to shape the future of online connections, we want to hear from you!
What You'll Do
  • Own the technical direction for Bumble's recommendations platform, evolving the systems that service recommendations for millions of members. Identify the highest-leverage engineering investments across retrieval, ranking, and serving, while balancing relevance, marketplace health, reliability, and latency.
  • Lead the design of large-scale distributed systems that power recommendations across multiple teams and domains. From online serving and feature delivery to experimentation and feedback loops, keep them simple, resilient, scalable, and elegant as the platform evolves.
  • Identify and solve the highest-leverage technical problems across the recommendations stack, bring clarity to ambiguous architectural decisions, and create solutions that help multiple teams move faster.
  • Raise the bar for engineering quality through technical leadership. Establish architectural principles, engineering standards, observability practices, and operational excellence that improve the quality and maintainability of systems across the organization.
  • Multiply the impact of other engineers by mentoring senior engineers, influencing technical direction across teams, and sharing context and judgment on the organization's most challenging engineering problems.
  • Drive platform evolution for the long term. Lead foundational initiatives such as service decomposition, recommendation infrastructure, experimentation capabilities, developer tooling, and AI-assisted engineering that enable the organization to move faster over time.
  • Remain deeply technical through hands-on contribution. Writing and reviewing high-quality code where it creates the greatest leverage. Contributing to critical designs, prototypes, and production code. Rapidly prototyping new ideas and serving as a trusted expert for the most critical parts of Bumble's recommendations platform.

About you
  • Typically requires 8+ years of building large-scale backend or distributed systems, with experience delivering complex technical initiatives that span multiple teams.
  • Deep expertise in designing and operating high-scale distributed systems, with strong experience in modern languages such as Go, Kotlin, Java, or similar, and a track record of building reliable production platforms.
  • Strong understanding of recommendation systems, ranking architectures, or other large-scale decision systems, including concepts such as retrieval, candidate generation, ranking, feature serving, experimentation, and feedback loops.
  • Experience building cloud-native systems on Google Cloud Platform (GCP) or comparable public cloud infrastructure, with deep knowledge of scalability, resilience, observability, and operational excellence.
  • Demonstrated ability to define technical strategy and influence architectural direction across multiple engineering teams through expertise, collaboration, and sound technical judgment rather than organizational authority.
  • Proven experience partnering closely with Product, Data Science, Machine Learning and Engineering leadership to translate ambiguous business problems into durable technical solutions.
  • A track record of mentoring senior engineers, raising engineering standards, and creating leverage by improving systems, tooling, architecture, and the effectiveness of the wider engineering organization.
  • Strong AI fluency, using modern AI-assisted engineering tools to improve productivity while applying thoughtful human judgment, maintaining high engineering standards, and ensuring member trust remains central to every technical decision.

Nice to Have
  • Experience building recommendation systems, search platforms, personalization engines, or other intelligent decision systems.
  • Experience with geospatial technologies, GIS platforms, routing systems, spatial databases (e.g., PostGIS), mapping APIs, GPS services, or other location-aware applications.
  • Experience building platforms or shared infrastructure used by multiple engineering teams.
  • Familiarity with experimentation platforms, feature delivery systems, event-driven architectures, or real-time data processing.
  • Experience building consumer-facing products at scale.

$255,000 - $285,000 a year
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.