ZipRecruiter

Log In

2

Flexible Remote Image Annotation Jobs in Florida

Danaher

Channel Sales Manager

Miami, FL · Remote

$145K/yr

Our advanced microscopes and AI-based image analysis solutions enable users to gain profound ... We recognize the benefits of flexible, remote working arrangements for eligible roles and are ...

EN Engineering LLC

Structural Designer

Tallahassee, FL · Remote

Fully Remote* *Candidates can be located anywhere in the U.S* Job Summary: The Designer should have ... Add annotation and dimensions to foundation location plans, sections, and details to PDF for review

ProTouch Staffing

Radiology Physician

Naples, FL · On-site +1

$301K - $377K/yr

Naples, Florida (Full-time; onsite or remote options available) Specialty: Diagnostic Radiology ... Additional flexible shift models may be accommodated (e.g., 4-day week, early start) Overview: We ...

House of Hearts Florida

Social Media Manager

Hollywood, FL · Remote

$15 - $20/hr

Remote (Florida-based candidates only) Industry: Behavioral Health / ABA Therapy Company: House of ... Design branded, visually engaging content using Canva and AI image tools * Create compelling UGC ...

All JobsImage Annotation JobsFlexible Remote Image Annotation JobsFlexible Remote Image Annotation Jobs in Florida

Flexible Remote Image Annotation information

What is flexible remote image annotation?

Flexible remote image annotation is a job where individuals label or tag elements within digital images from a remote location, often from home. This work is crucial for training artificial intelligence and machine learning models, particularly in fields like computer vision and autonomous vehicles. The 'flexible' aspect means workers can often set their own hours and choose tasks according to their availability. Image annotation tasks may include outlining objects, assigning categories, or describing visual content in images. Most positions require attention to detail and basic computer skills, but prior experience is not always necessary.

What are the key skills and qualifications needed to thrive as a Flexible Remote Image Annotation Specialist, and why are they important?

To thrive as a Flexible Remote Image Annotation Specialist, you need strong attention to detail, visual accuracy, and a basic understanding of image processing, often supported by a high school diploma or equivalent. Familiarity with annotation tools such as Labelbox, CVAT, or VIA, and sometimes experience with basic data entry platforms, is typically required. Excellent time management, communication skills, and the ability to work independently are valued soft skills for this remote role. These skills ensure high-quality, consistent data labeling essential for training reliable machine learning models and supporting AI development.

What are some common challenges faced in flexible remote image annotation roles and how can they be managed?

One common challenge in flexible remote image annotation is maintaining accuracy and consistency across large datasets, especially when guidelines are complex or images are ambiguous. Working independently can also make it harder to get immediate feedback or clarification. To manage these challenges, it’s important to regularly review annotation guidelines, participate in team check-ins or forums, and make use of quality assurance tools provided by the employer. Staying organized and communicating proactively with project leads can help ensure your work meets expectations and deadlines.

What is the difference between Flexible Remote Image Annotation vs Data Labeler?

AspectFlexible Remote Image AnnotationData Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote, flexible hoursRemote, flexible hours
Industry UsageAI, machine learning, computer visionAI, machine learning, data processing
Job FocusAnnotating images with labels, bounding boxes, segmentationLabeling data, categorizing images or text

Flexible Remote Image Annotation and Data Labeler roles both involve data processing tasks in AI and machine learning industries. While image annotation focuses on marking specific features within images, data labelers may work with various data types, including text and images. Both roles are remote, require similar skills, and serve the same industry needs, but image annotation emphasizes visual data precision.

What are the most commonly searched types of Remote Image Annotation jobs in Florida? The most popular types of Remote Image Annotation jobs in Florida are:
What are popular job titles related to Flexible Remote Image Annotation jobs in Florida? For Flexible Remote Image Annotation jobs in Florida, the most frequently searched job titles are:
What job categories do people searching Flexible Remote Image Annotation jobs in Florida look for? The top searched job categories for Flexible Remote Image Annotation jobs in Florida are:
What cities in Florida are hiring for Flexible Remote Image Annotation jobs? Cities in Florida with the most Flexible Remote Image Annotation job openings:
Flexible Remote Image Annotation jobs near you
Infographic showing various Flexible Remote Image Annotation job openings in Florida as of July 2026, with employment types broken down into 77% Full Time, 17% Part Time, 2% Temporary, and 4% Contract. Highlights an 2% In-person, and 98% Remote job distribution.

SENIOR COMPUTER VISION ENGINEER - REMOTE SENSING VACANCY - Satlantis

SATLANTIS

Gainesville, FL • On-site, Remote

$94K - $130K/yr

Full-time

Re-posted 19 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