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Remote Machine Vision Engineer Jobs in Florida (NOW HIRING)

OptiTrack

Machine Learning & Operations Engineer

Miami, FL · Remote

$66K - $89K/yr

This is a fully remote position, working cross-functionally with research and engineering teams ... Experience with motion capture or computer vision systems * Familiarity with experiment tracking ...

OptiTrack

Machine Learning & Operations Engineer

Miami, FL · Remote

$66K - $89K/yr

This is a fully remote position, working cross-functionally with research and engineering teams ... Experience with motion capture or computer vision systems * Familiarity with experiment tracking ...

ClifyX

Sr. Machine Learning Engineer

Bradenton, FL · Remote

$111K - $146K/yr

The ability to work collaboratively with remote teams. * Experience with containerization using ... Specific vision abilities required by this job include close vision, and ability to adjust focus.

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Remote Machine Vision Engineer information

How do Remote Machine Vision Engineers typically collaborate with cross-functional teams given the remote nature of the role?

Remote Machine Vision Engineers often work closely with software developers, hardware engineers, and project managers through virtual meetings, collaborative platforms, and shared code repositories. Effective communication is essential to ensure alignment on project goals, technical specifications, and integration challenges. Regular video conferences, clear documentation, and agile project management tools help maintain productivity and foster team cohesion, despite being geographically dispersed.

What does a Remote Machine Vision Engineer do?

A Remote Machine Vision Engineer designs, develops, and implements computer vision systems that enable machines to interpret visual information, often working from a remote location. Their tasks include creating algorithms for image processing, integrating hardware like cameras, and collaborating with teams to solve automation or inspection challenges. They may work in industries such as manufacturing, robotics, or healthcare, using technologies like deep learning and neural networks. Remote Machine Vision Engineers typically use tools such as Python, OpenCV, and TensorFlow, and communicate with their teams via digital platforms. This role requires both strong programming skills and a deep understanding of image analysis techniques.

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

To thrive as a Remote Machine Vision Engineer, you need expertise in computer vision, image processing, programming (such as Python or C++), and a relevant engineering or computer science degree. Familiarity with frameworks like OpenCV, deep learning libraries (TensorFlow or PyTorch), and experience with cloud-based collaboration tools are typically required. Strong problem-solving abilities, self-motivation, and effective remote communication skills help you excel in this role. These skills ensure the accurate design and deployment of vision solutions while maintaining productivity and collaboration in a remote work environment.
What are the most commonly searched types of Machine Vision Engineer jobs in Florida? The most popular types of Machine Vision Engineer jobs in Florida are:
What are popular job titles related to Remote Machine Vision Engineer jobs in Florida? For Remote Machine Vision Engineer jobs in Florida, the most frequently searched job titles are:
What job categories do people searching Remote Machine Vision Engineer jobs in Florida look for? The top searched job categories for Remote Machine Vision Engineer jobs in Florida are:
What cities in Florida are hiring for Remote Machine Vision Engineer jobs? Cities in Florida with the most Remote Machine Vision Engineer job openings:
Remote Machine Vision Engineer jobs near you

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