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Remote Robotics Research Engineer Jobs in Florida

Synnex

Physical AI Engineer

Clearwater, FL · On-site +1

Remote or hybrid, US-based, with periodic time onsite at our robotics facility. * Occasional ... engineers with strong reinforcement learning and simulation expertise. At TD SYNNEX, our values ...

Phsorg

$87K - $149K/yr

Remote AI Automation Developer Summary: Build your Career. Make a Difference. Presbyterian is ... Develop and deploy scalable RPA, workflow automation, and AI-powered conversational solutions.

Booz Allen Hamilton, Inc.

Data Engineer, Senior

Tampa, FL · On-site +1

$99K - $225K/yr

Remote Work: No Job Number: R0245470 Location: Tampa,FL,US Share job via: Share Data Engineer ... TS/SCI clearance * Master's degree in Mathematics, Operations Research, Engineering, or Data ...

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All JobsRobotics Research Engineer JobsRemote Robotics Research Engineer JobsRemote Robotics Research Engineer Jobs in Florida

Remote Robotics Research Engineer information

What is the difference between Remote Robotics Research Engineer vs Remote Robotics Software Developer?

AspectRemote Robotics Research EngineerRemote Robotics Software Developer
Required CredentialsMaster's or PhD in Robotics, Mechanical, or Electrical EngineeringBachelor's or Master's in Computer Science or Software Engineering
Work EnvironmentResearch labs, universities, R&D departmentsTech companies, startups, industrial firms
Industry UsageResearch, academia, innovation projectsProduct development, software solutions, automation
Common Search/ComparisonFocuses on research and innovation in roboticsFocuses on software development for robotics applications

The main difference is that Remote Robotics Research Engineers focus on advancing robotics technology through research and experimentation, often working in academic or R&D settings. In contrast, Remote Robotics Software Developers primarily develop and implement software solutions for robotic systems in industry. Both roles require technical skills, but their goals and work environments differ significantly.

What are the key skills and qualifications needed to thrive as a remote robotics research engineer?

To thrive as a Remote Robotics Research Engineer, you need a strong background in robotics, computer science, and mathematics, often supported by an advanced degree in a related field. Proficiency in programming languages such as Python or C++, robotics frameworks like ROS, and simulation tools such as Gazebo or MATLAB is typically required. Exceptional problem-solving, self-motivation, and effective virtual communication are crucial soft skills for collaborating and innovating remotely. These skills and qualities are vital for developing cutting-edge robotics solutions and ensuring smooth teamwork across distributed environments.

How does collaboration typically work for a remote robotics research engineer, and what tools are commonly used for remote teamwork?

As a Remote Robotics Research Engineer, you’ll frequently collaborate with multidisciplinary teams that may include software developers, mechanical engineers, and data scientists. Communication and project management are facilitated through tools like Slack, Microsoft Teams, and project tracking platforms such as Jira or Asana. Version control and code collaboration often occur via GitHub or GitLab. Regular virtual meetings, code reviews, and shared documentation ensure alignment and productivity despite the physical distance, making strong communication skills and self-motivation essential for success in this remote environment.

What is a remote robotics research engineer?

Remote Robotics Research Engineers are professionals who design, develop, and test robotic systems while working from a remote or virtual location. They use advanced programming skills, simulation tools, and data analysis to create robots or autonomous systems for various industries, such as manufacturing, healthcare, or space exploration. Their responsibilities often include conducting research, collaborating with cross-functional teams, and publishing their findings, all while utilizing cloud-based platforms and remote communication tools. This role is ideal for individuals with strong technical backgrounds who seek flexibility and global collaboration opportunities.
What are the most commonly searched types of Robotics Research Engineer jobs in Florida? The most popular types of Robotics Research Engineer jobs in Florida are:
What are popular job titles related to Remote Robotics Research Engineer jobs in Florida? For Remote Robotics Research Engineer jobs in Florida, the most frequently searched job titles are:
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Remote Robotics Research Engineer jobs near you

SENIOR COMPUTER VISION ENGINEER - REMOTE SENSING VACANCY - Satlantis

SATLANTIS

Gainesville, FL • On-site, Remote

$94K - $130K/yr

Full-time

Re-posted 24 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/ .

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