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Computer Vision Researcher Jobs in Florida (NOW HIRING)

Prophecy Technologies

Generative AI Engineer

Tampa, FL · On-site

Build and optimize deep learning, NLP, or computer vision models depending on project requirements ... Research and apply the latest developments in AI and machine learning. * Ensure scalability ...

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All JobsComputer Vision Researcher JobsComputer Vision Researcher Jobs in Florida

Computer Vision Researcher information

See Florida salary details

$22.4K

$84.5K

$122.9K

How much do computer vision researcher jobs pay per year?

As of Jun 19, 2026, the average yearly pay for computer vision researcher in Florida is $84,520.00, according to ZipRecruiter salary data. Most workers in this role earn between $50,100.00 and $115,100.00 per year, depending on experience, location, and employer.

What does a Computer Vision Researcher do?

A Computer Vision Researcher develops algorithms and models that enable computers to interpret and understand visual information from the world, such as images and videos. They work on tasks like object detection, image segmentation, and facial recognition, often using techniques from machine learning and artificial intelligence. Their work is applied in fields such as autonomous vehicles, medical imaging, robotics, and augmented reality. Computer Vision Researchers typically conduct experiments, publish scientific papers, and collaborate with engineers to implement their findings in real-world applications.

What are some common challenges faced by Computer Vision Researchers when transitioning from theoretical research to practical applications?

Computer Vision Researchers often encounter challenges when moving from theoretical models to real-world deployment, such as dealing with noisy or incomplete data, ensuring scalability, and optimizing models for real-time performance. Collaborative work with software engineers and domain experts is crucial to address these issues and to adapt state-of-the-art algorithms for production environments. Additionally, staying updated with rapidly evolving tools and frameworks is essential for successfully bridging the gap between research and application.

What is the difference between Computer Vision Researcher vs Machine Learning Engineer?

AspectComputer Vision ResearcherMachine Learning Engineer
Required CredentialsMaster's or PhD in Computer Science, AI, or related fieldsBachelor's or Master's in Computer Science, Data Science, or related fields
Work EnvironmentResearch labs, academia, R&D departmentsTech companies, startups, product teams
Employer & Industry UsageUniversities, research institutions, AI-focused companiesTechnology firms, software companies, AI product development
Common Search & ComparisonYesYes

While both roles involve AI and machine learning, a Computer Vision Researcher primarily focuses on developing algorithms for visual data analysis and often works in research settings. In contrast, a Machine Learning Engineer applies machine learning techniques to build scalable AI products and solutions in industry environments.

What are the key skills and qualifications needed to thrive as a Computer Vision Researcher, and why are they important?

To thrive as a Computer Vision Researcher, you need a strong background in mathematics, machine learning, image processing, and typically a graduate degree in computer science or a related field. Experience with deep learning frameworks (such as TensorFlow or PyTorch), programming languages (like Python or C++), and familiarity with relevant research publications are highly valued. Creativity, problem-solving abilities, and strong communication skills help researchers innovate and effectively share findings. These competencies are vital for advancing technology, developing novel algorithms, and collaborating within multidisciplinary teams.
What are popular job titles related to Computer Vision Researcher jobs in Florida? For Computer Vision Researcher jobs in Florida, the most frequently searched job titles are:
What job categories do people searching Computer Vision Researcher jobs in Florida look for? The top searched job categories for Computer Vision Researcher jobs in Florida are:
Computer Vision Researcher jobs near you
Infographic showing various Computer Vision Researcher job openings in Florida as of June 2026, with employment types broken down into 23% Internship, 54% Full Time, and 23% Temporary. Highlights an 100% In-person job distribution, with an average salary of $84,520 per year, or $40.6 per hour.

SENIOR COMPUTER VISION ENGINEER - REMOTE SENSING VACANCY - Satlantis

SATLANTIS

Gainesville, FL • On-site, Remote

$94K - $130K/yr

Full-time

Posted 5 days ago

Job description

Satlantis is a leading-edge company specializing in high-performance satellite technology and data processing. We are at the forefront of innovation, developing advanced solutions for Earth observation and space exploration. Join our dynamic team in Gainesville, Florida, and contribute to groundbreaking projects that shape the future of satellite technology. For more information about the company, please visit www.satlantis.com .
Position Summary
We are seeking a highly motivated and experienced Senior Computer Vision Engineer with strong technical leadership to drive Satlantis US's computer vision and imagery understanding initiatives. The ideal candidate combines deep expertise in modern vision systems with pragmatic delivery: you will design, develop, evaluate, and deploy computer vision models and pipelines that operate on large-scale satellite imagery and geospatial data products.
This is a hands-on role where you will own vision workstreams end-to-end-from problem definition and dataset strategy to model development, production deployment, performance optimization, and iteration-while setting engineering standards, mentoring teammates, and partnering closely with engineering, product, and mission teams. You will help ensure our computer vision systems are accurate, robust, scalable, and operationally effective in real-world Earth-observation workflows.
What you'll do:
  • Own your developments. Lead high-impact computer vision initiatives such as segmentation, object detection, classification, image matching, semantic retrieval, change detection, tracking, and anomaly detection over satellite imagery and derived geospatial products, delivering measurable improvements in model quality and operational outcomes.
  • Translate problems into vision systems. Convert customer needs, mission requirements, and research goals into well-scoped computer vision problems, define success metrics and KPIs (e.g. precision/recall, mAP, IoU, F1, latency, throughput, memory footprint), and establish acceptance criteria and validation plans.
  • Design datasets that win. Drive dataset strategy for vision applications, including annotation protocols, tiling and sampling strategies, class balance, hard-negative mining, augmentation policies, domain-shift analysis, and label-quality audits. Establish repeatable dataset versioning and documentation practices.
  • Build robust training and evaluation pipelines. Implement reproducible experimentation, benchmarking, ablation studies, and error-analysis workflows for computer vision models, including geospatially aware evaluation where applicable.
  • Advance model architectures. Develop and improve state-of-the-art computer vision approaches, including CNNs, transformers, encoder-decoder architectures, self-supervised learning, multi-modal fusion, and foundation-model adaptation for remote sensing imagery. Optimize solutions for real operational constraints such as image resolution, viewing conditions, atmospheric noise, and multi-temporal data.
  • Operationalize vision models. Partner with software and platform engineers to productionize vision systems, including model packaging, inference optimization, deployment pipelines, monitoring, drift detection, versioning, rollback strategies, and performance tuning across heterogeneous compute environments.
  • Raise the engineering bar. Set standards for code quality, reproducibility, model validation, benchmarking, documentation, and peer review. Write clear technical design documents and decision memos that align stakeholders and accelerate execution.

Skills and experience (required):
  • Bachelor's, Master's, or PhD in Computer Science, Computer Engineering, Electrical Engineering, Remote Sensing, Robotics, or a related field.
  • 3+ years of professional experience in computer vision, machine learning, or applied AI, including delivering vision models into production or operational workflows.
  • Strong proficiency in Python for machine learning and computer vision workflows; ability to write clean, maintainable, and well-tested code.
  • Deep knowledge of computer vision fundamentals, including image representations, feature extraction, geometric reasoning, dense prediction, detection, segmentation, and model evaluation.
  • Hands-on experience with deep learning frameworks such as PyTorch (preferred) or TensorFlow, and practical experience implementing modern vision architectures.
  • Strong understanding of training and inference optimization, including data loading efficiency, batching, mixed precision, model compression, and performance-aware experimentation.
  • Experience working with large-scale imagery or visual datasets and building pipelines that are reliable and reproducible.
  • Strong communication skills, with the ability to explain complex technical trade-offs clearly to cross-functional stakeholders.

Nice to have (preferred)
  • Geospatial / satellite domain experience: GDAL, Rasterio, projections/CRS, tiling strategies, GeoTIFF/COG/NetCDF, STAC/PgSTAC, and geospatial image-quality considerations.
  • Remote-sensing computer vision: experience with multi-spectral or panchromatic imagery, super-resolution, image fusion, orthorectification-aware workflows, and change detection in Earth-observation contexts.
  • Spatiotemporal vision modeling: time-series imagery, temporal fusion, motion/change analysis, event detection, or tracking across repeated satellite captures.
  • MLOps / production AI: model serving, monitoring, experiment tracking (e.g. W&B, MLflow, CometML), orchestration (Airflow, Argo, ZenML), and lifecycle management.
  • Cloud & compute: experience training and running inference on AWS/GCP/Azure and on-prem HPC/cluster environments, including SLURM-managed GPU/CPU fleets and Kubernetes-based infrastructure; strong understanding of containers, distributed training, GPU scheduling, storage/performance bottlenecks, and cost/performance tuning.
  • Foundation models for vision / Earth observation: fine-tuning, embedding extraction, retrieval systems, transfer learning, promptable models, and multimodal representation learning.
  • C++ or performance-oriented deployment experience: OpenCV, ONNX, TensorRT, Triton Inference Server, CUDA optimization, or edge/real-time inference workflows.
  • Familiarity with data governance and quality frameworks, including lineage, validation checks, and dataset documentation.

Work Authorization:
This role will not sponsor any employment visas. Candidates must have and maintain unrestricted legal authorization to work in the U.S. now and in the future, without requiring employer-sponsored visa support.
Location & Work Model:
Full-time, in-person position in Gainesville, Florida. You'll work closely with engineering and business teams on impactful, real-world satellite analytics and AI systems-helping deliver reliable, scalable capabilities that push forward the state of the art in Earth observation.
Why Join Satlantis?
  • Be part of a pioneering company at the forefront of space technology.
  • Work on challenging and impactful projects that have real-world applications.
  • Collaborate with a team of brilliant and passionate engineers and scientists.
  • Competitive salary and benefits package.
  • Opportunity for professional growth and development in a rapidly expanding industry.
  • Enjoy the vibrant community and quality of life in Gainesville, Florida. Learn more at https://www.visitgainesville.com/ .

Apply