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Computer Vision Engineer Jobs in Gainesville, FL

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Computer Vision Engineer information

See Gainesville, FL salary details

$43.9K

$110.1K

$124.6K

How much do computer vision engineer jobs pay per year?

As of May 29, 2026, the average yearly pay for computer vision engineer in Gainesville, FL is $110,093.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,000.00 and $119,100.00 per year, depending on experience, location, and employer.

What Does a Computer Vision Engineer Do?

Computer vision is a branch of artificial intelligence that attempts to replicate human analytical processes by using algorithms and computer models to understand and identify patterns in images. As a computer vision engineer, you use software to handle the processing and analysis of large data populations, and your efforts support the automation of predictive decision-making efforts. Your responsibilities involve research, programming, data analysis, and user interface design. You may work on a variety of exciting development projects like self-driving cars, mobile devices, innovative features and capabilities in sports and entertainment, and the next generation of social media enhancements.

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

To thrive as a Computer Vision Engineer, you need a strong background in computer science, mathematics, and machine learning, often supported by a relevant degree and experience with image processing algorithms. Familiarity with tools and frameworks such as OpenCV, TensorFlow, PyTorch, and proficiency in programming languages like Python or C++ is essential, along with knowledge of deep learning techniques. Analytical thinking, creativity, and effective communication are standout soft skills for this role. These skills and qualities are crucial for developing innovative vision solutions, interpreting complex data, and collaborating efficiently within interdisciplinary teams.

What are some common challenges faced by Computer Vision Engineers when deploying models to production environments?

Computer Vision Engineers often encounter challenges such as ensuring model accuracy in diverse real-world conditions, optimizing models for efficiency on edge devices, and handling large-scale data processing. Deploying models to production requires balancing performance with resource constraints and addressing issues like latency, scalability, and data privacy. Collaborating closely with software engineers and data scientists is crucial to integrate solutions effectively and continuously monitor and improve model performance in live applications.

What are Computer Vision Engineers?

Computer Vision Engineers are professionals who develop algorithms and systems that enable computers to interpret and process visual information from the world, such as images and videos. They work on tasks like object detection, facial recognition, image segmentation, and more, often using machine learning and deep learning techniques. These engineers apply their expertise in fields like robotics, autonomous vehicles, healthcare, and augmented reality, turning raw visual data into actionable insights.

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

AspectComputer Vision EngineerMachine Learning Engineer
Required CredentialsBachelor's or Master's in CS, Electrical Engineering, or related; knowledge of image processing and computer vision librariesBachelor's or Master's in CS, Data Science, or related; strong programming and statistical skills
Work EnvironmentDevelops algorithms for image/video analysis, object detection, and recognition in tech, automotive, or healthcare industriesBuilds models for various data types, including text, images, and structured data across multiple sectors
Employer & Industry UsageTech companies, autonomous vehicles, robotics, healthcareTech firms, finance, e-commerce, healthcare, and research institutions

While both roles involve machine learning techniques, Computer Vision Engineers specialize in developing algorithms for visual data, whereas Machine Learning Engineers work on broader data modeling across various data types. The roles often overlap but differ mainly in focus and application areas.

What cities near Gainesville, FL are hiring for Computer Vision Engineer jobs? Cities near Gainesville, FL with the most Computer Vision Engineer job openings:
Infographic showing various Computer Vision Engineer job openings in Gainesville, FL as of May 2026, with employment types broken down into 2% Internship, 96% Full Time, and 2% Contract. Highlights an 88% In-person, 3% Hybrid, and 9% Remote job distribution, with an average salary of $110,093 per year, or $52.9 per hour.

SENIOR COMPUTER VISION ENGINEER - REMOTE SENSING VACANCY - Satlantis

SATLANTIS

Gainesville, FL โ€ข On-site, Remote

$94.70K - $130K/yr

Full-time

Posted 14 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/ .