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Remote Machine Learning Jobs in Gainesville, FL (NOW HIRING)

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Remote Machine Learning information

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$23.1K

$38.6K

$79.7K

How much do remote machine learning jobs pay per year?

As of Jul 21, 2026, the average yearly pay for remote machine learning in Gainesville, FL is $38,581.00, according to ZipRecruiter salary data. Most workers in this role earn between $29,400.00 and $41,700.00 per year, depending on experience, location, and employer.

What engineer makes $500,000 a year?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data modeling, and often working at large tech companies or in specialized industries can earn salaries approaching or exceeding $500,000 annually. Compensation may include base salary, bonuses, and stock options, especially in high-demand markets.

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

To thrive as a Remote Machine Learning Engineer, you need a strong background in mathematics, statistics, programming (often Python), and experience with machine learning frameworks, typically supported by a relevant degree. Familiarity with tools such as TensorFlow, PyTorch, cloud platforms (like AWS or GCP), and version control systems is crucial. Strong problem-solving abilities, self-management, and effective virtual communication distinguish top performers in remote settings. These competencies ensure the engineer can build effective models, collaborate across distributed teams, and deliver impactful solutions independently.

How to make 2000 a week working from home?

Remote machine learning professionals can earn $2,000 or more weekly by taking on high-paying freelance projects, consulting roles, or working for companies that offer remote positions with competitive salaries. Building specialized skills in programming, data analysis, and tools like Python, TensorFlow, or cloud platforms can increase earning potential. Consistent work, a strong portfolio, and networking are key to reaching this income level from home.

What Are Remote Machine Learning Jobs?

Machine learning is a method of analyzing data via automating analytical model building. The premise is that systems can learn from data. Machine learning positions include machine learning engineer, computer vision engineer, and senior deep learning engineer. In a remote machine learning job, you work from home in a branch of artificial intelligence performing duties related to computational processing and data. Your goal is to design models that solve business problems, such as helping organizations avoid unknown risks or find profitable opportunities. Your responsibilities include maintaining data pipelines, performing model research and implementation, building machine learning systems, and onboarding new utilities.

What is a remote machine learning job?

A remote machine learning job involves working with algorithms, data, and models to develop predictive systems or automate tasks, all while working from a location outside of a traditional office setting. Professionals in this role use techniques from statistics and computer science to analyze data, train machine learning models, and deploy solutions for real-world applications. Remote machine learning jobs can span various industries, including technology, healthcare, finance, and e-commerce. These roles typically require strong programming skills, knowledge of machine learning frameworks, and the ability to communicate findings effectively with team members or stakeholders. Working remotely offers flexibility, but also requires discipline and self-motivation to succeed.

What are some effective strategies for collaborating with team members while working remotely as a Machine Learning Engineer?

Collaboration in a remote Machine Learning role often relies on clear communication through digital tools such as Slack, Zoom, and project management platforms like Jira or Asana. Regular check-ins and stand-up meetings help keep everyone aligned on project goals and timelines. Sharing code and models via version control systems (like Git) and using collaborative notebooks (such as JupyterHub or Google Colab) are also common practices. Building strong documentation habits and proactively seeking feedback can help ensure smooth teamwork and project success, even across different time zones.

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

AspectRemote Machine LearningData Scientist
Required CredentialsBachelor's/Master's in CS, ML certificationsBachelor's/Master's in CS, Statistics, or related field
Work EnvironmentRemote, collaborative teams, tech companiesRemote or on-site, diverse industries, analytics focus
Industry UsageTech, AI startups, researchFinance, healthcare, e-commerce, tech
Search & Comparison IntentOften compared for technical roles in AI/MLBroader data analysis roles, but overlapping skills

Remote Machine Learning specialists focus on developing algorithms and models primarily in tech environments, often requiring advanced programming and ML knowledge. Data Scientists analyze data to extract insights, sometimes utilizing ML techniques. While both roles share skills and credentials, Remote Machine Learning emphasizes model development, whereas Data Scientists focus on data analysis and interpretation.

Are there remote machine learning jobs?

Yes, remote machine learning jobs are widely available across various industries, often requiring skills in programming, data analysis, and familiarity with tools like Python, TensorFlow, or PyTorch. Many companies offer flexible schedules and remote work options for qualified candidates, especially in tech and research sectors.

Will MLE be replaced by AI?

Machine Learning Engineers (MLEs) design, develop, and deploy AI models, and their role involves understanding algorithms, data preprocessing, and model optimization. While AI automation tools can handle certain tasks, MLEs are essential for creating, fine-tuning, and maintaining complex AI systems, making complete replacement unlikely in the near term.
More about Remote Machine Learning jobs
What are the most commonly searched types of Machine Learning jobs in Gainesville, FL? The most popular types of Machine Learning jobs in Gainesville, FL are:
What are popular job titles related to Remote Machine Learning jobs in Gainesville, FL? For Remote Machine Learning jobs in Gainesville, FL, the most frequently searched job titles are:
What cities near Gainesville, FL are hiring for Remote Machine Learning jobs? Cities near Gainesville, FL with the most Remote Machine Learning job openings:
Remote Machine Learning jobs near you
Infographic showing various Remote Machine Learning job openings in Gainesville, FL as of July 2026, with employment types broken down into 1% As Needed, 66% Full Time, 31% Part Time, 1% Temporary, and 1% Contract. Highlights an 89% Physical, 1% Hybrid, and 10% Remote job distribution, with an average salary of $38,581 per year, or $18.5 per hour.
Postdoctoral Research Associate: GeoAI and Remote Sensing for Invasive Species Ecology

Postdoctoral Research Associate: GeoAI and Remote Sensing for Invasive Species Ecology

University of Florida

Gainesville, FL • On-site, Remote

Full-time

Re-posted 8 days ago

University Of Florida rating

7.2

Company rating: 7.2 out of 10

Based on 108 frontline employees who took The Breakroom Quiz

345th of 555 rated colleges and universities

Job description

Postdoctoral Research Associate: GeoAI and Remote Sensing for Invasive Species Ecology
Job no: 537559
Work type: Post Doc Associate
Location: Main Campus (Gainesville, FL)
Categories: Computer Science, Grant or Research Administration, Artificial Intelligence, Physical/Mathematical Sciences
Department:16220000 - LS-GEOGRAPHY
Classification Title:
Postdoctoral Associate
Classification Minimum Requirements:
  • A Ph.D. (by the start date) in Remote Sensing, Geography, Biology, Geospatial Science, Environmental Science, Ecology, or a closely related field.
  • Demonstrated expertise in processing and analyzing remote sensing data (hyperspectral and/or Lidar is a strong plus).
  • Strong proficiency in programming, particularly in Python and GEE for geospatial analysis and data science.
  • Experience with machine learning/deep learning frameworks (e.g., PyTorch, TensorFlow) applied to image or geospatial data.
  • A track record of first-author publications in peer-reviewed journals.
  • Excellent communication, collaboration, and writing skills.

Job Description:
The Geospatial Artificial Intelligence (GeoAI) Lab at the University of Florida, led by Dr. Di Yang, is seeking a highly motivated Postdoctoral Research Associate to join a new, multi-institutional research project focused on the invasive grass Ventenata dubia (VEDU). This project is a collaboration with leading experts at the University of Montana (Spatial Analysis Lab) and Boise State University.
The successful candidate will lead the development and implementation of cutting-edge remote sensing and machine learning techniques to address critical questions about invasive species surveillance and invasion dynamics. Key research themes include: 1) characterizing invasion resistance, 2) assessing the role of phenotypic plasticity in its competitive success, and 3) developing robust methods for spectral phenotyping using ground, drone, and satellite-based sensors. This position offers a unique opportunity to work at the intersection of remote sensing, spectranomics, genetic analysis, GeoAI, and invasion ecology within a dynamic, collaborative team.
Responsibilities:
  • Design and lead remote sensing data acquisition campaigns using multi-scale platforms, including ground-based spectrometers, UAVs (optical, Lidar), and satellite imagery (e.g., Planet, Sentinel, Landsat).
  • Develop and apply advanced machine learning and deep learning models (GeoAI) for fusing, analyzing, and interpreting multi-sensor data to track invasion species patterns
  • Create novel analytical workflows to build calibration equations for discriminating VEDU from other co-occurring grass species.
  • Integrate remote sensing-derived products with in-situ ecological data (e.g., canopy cover, height, alpha diversity, chemistry, soil texture, disturbance intensity) to model invasion dynamics and resilience across landscapes.
  • Collaborate closely with project partners to synthesize findings and build follow-on funding opportunities.
  • Lead the preparation of high-impact, peer-reviewed publications.
  • Present research findings at national and international scientific conferences.
  • Mentor graduate and undergraduate student in the GeoDI (Geospatial Digital Informatics) Lab.
UF is the state's oldest, largest, and most comprehensive land grant university with an enrollment of over 50,000 students and was ranked 7th in the country among public universities (US News and World Report 2025 rankings), and 1st among public institutions in the Wall Street Journal 2023 survey. UF is located in Gainesville, a city of approximately 150,000 residents in North-Central Florida, 50 miles from the Gulf of Mexico, and 67 miles from the Atlantic Ocean, and within a 2-hour drive to large metropolitan areas (Orlando, Tampa, Jacksonville). The beautiful climate and extensive nearby parks and recreational areas afford year-round outdoor activities, including hiking, biking, and nature photography. UF's large college sports programs, museums, and performing arts center support a range of activities and cultural events for residents to enjoy. Alachua County schools are highly rated and offer a variety of programs including magnet schools and an international baccalaureate program. Learn more about what Gainesville has to offer at Visit Gainesville.
Expected Salary:
The salary is competitive and commensurate with qualifications and experience, and the compensation includes a full benefits package. To see more, visit, benefits.hr.ufl.ed.
Required Qualifications:
  • A Ph.D. (by the start date) in Remote Sensing, Geography, Biology, Geospatial Science, Environmental Science, Ecology, or a closely related field.
  • Demonstrated expertise in processing and analyzing remote sensing data (hyperspectral and/or Lidar is a strong plus).
  • Strong proficiency in programming, particularly in Python and GEE for geospatial analysis and data science.
  • Experience with machine learning/deep learning frameworks (e.g., PyTorch, TensorFlow) applied to image or geospatial data.
  • A track record of first-author publications in peer-reviewed journals.
  • Excellent communication, collaboration, and writing skills.

Preferred:
  • Experience in plant ecology, invasion science, or agronomy.
  • Specific expertise in reflectance spectroscopy and chemometrics for vegetation analysis or high-throughput phenotyping.
  • A strong background in GeoAI, computer vision, and data fusion techniques.
  • Experience designing UAV-based remote sensing campaigns.
  • Experience leading ground-based vegetation surveys.
  • Demonstrated ability to work effectively in a collaborative, interdisciplinary research team.

Special Instructions to Applicants:
For full consideration, applications must be submitted online. Click on Apply Now at the top of this posting.
A complete application includes (1) a letter (max 2 pages) of application summarizing the applicant's qualifications, interests, and suitability for the position, (2) a complete curriculum vitae, (3) a statement on research goals, and (4) a list of three references. After initial review, letters of recommendation will be requested from the references for selected applicants.
Applications will be reviewed on a rolling basis starting immediately and will continue until the position is filled. The intended start date is flexible, ideally for the Spring 2026 semester. This is a full-time, 12-month appointment with the potential based on performance and funding availability.
Review of applications will be conducted on a rolling basis, with the first review beginning on November 15th.
All candidates for employment are subject to a pre-employment screening which includes a review of criminal records, reference checks, and verification of education.
The selected candidate will be required to provide an official transcript to the hiring department upon hire. A transcript will not be considered "official" if a designation of "Issued to Student" is visible. Degrees earned from an educational institution outside of the United States require evaluation by a professional credentialing service provider approved by the National Association of Credential Evaluation Services (NACES), which can be found at http://www.naces.org/.
Health Assessment Required:No
Advertised: 16 Oct 2025 Eastern Daylight Time
Applications close:
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The University of Florida is one of the top ranked public universities in the United States (ranked top 5 amongst public universities in 2023 US news and world report). It is one of only a few comprehensive universities, having medical, veterinary, dental, nursing, public health, and engineering disciplines all co-localized on the same, contiguous campus to facilitate interdisciplinary collaboration. Gainesville is located in the northern region of Florida, within 1-1.5 hours of each coast, and just 1.5-2 hours to Orlando and Tampa. It is a small to medium-sized city with a low cost of living, excellent public and private schools, and southern hospitality. While Gainesville is widely recognized as the home of the Gators, it is quickly becoming known as a center for innovation and a place with a lifestyle that's comfortable for families, yet attractive for young professionals.

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Colleges, universities, and professional schools

Company size

5,001 - 10,000 Employees

Headquarters location

Gainesville, FL, US

Year founded

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