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Remote Python Trading Jobs in Florida (NOW HIRING)

JLL

Senior Analytics Specialist

Tallahassee, FL · Remote

Whether you've got deep experience in commercial real estate, skilled trades or technology, or you ... Proficiency in Python/PySpark for data analysis and transformation * Experience with cloud-based ...

JLL

Senior Analytics Specialist

Pensacola, FL · Remote

Whether you've got deep experience in commercial real estate, skilled trades or technology, or you ... Proficiency in Python/PySpark for data analysis and transformation * Experience with cloud-based ...

All JobsPython Trading JobsRemote Python Trading JobsRemote Python Trading Jobs in Florida

Remote Python Trading information

What is remote python trading?

A Remote Python Trading job involves developing, maintaining, and optimizing trading algorithms or systems using the Python programming language, all while working remotely. Professionals in this role typically work for financial institutions, hedge funds, or fintech companies, analyzing market data, building automated trading strategies, and ensuring their code runs efficiently and securely. Strong programming skills in Python, knowledge of financial markets, and experience with trading platforms or APIs are essential. The remote nature of the job allows professionals to work from anywhere with a reliable internet connection.

What is the difference between Remote Python Trading vs Remote Quantitative Analyst?

AspectRemote Python TradingRemote Quantitative Analyst
Required CredentialsPython programming, finance knowledge, data analysis skillsMathematics, statistics, programming, finance or economics degree
Work EnvironmentFinancial firms, hedge funds, trading companiesFinancial institutions, investment firms, research organizations
Industry UsageHigh in trading and algorithm developmentHigh in risk modeling and quantitative research
Common Search/ComparisonYesYes

Remote Python Trading focuses on developing trading algorithms using Python, primarily in trading firms. Remote Quantitative Analysts work on financial modeling and risk analysis, often requiring similar skills but with a broader focus on quantitative research. Both roles involve programming and finance, but their core responsibilities differ in application and industry emphasis.

What are the key skills and qualifications needed to thrive as a remote python trading professional?

To thrive as a Remote Python Trading professional, you need strong proficiency in Python programming, quantitative analysis, and a solid understanding of financial markets, often supported by a relevant degree in finance, mathematics, or computer science. Experience with trading platforms, APIs, backtesting frameworks, and familiarity with libraries like pandas, NumPy, and scikit-learn are typically required. Analytical thinking, problem-solving, and effective remote communication are essential soft skills for success in this role. These skills enable the development of robust trading algorithms, effective risk management, and seamless collaboration in a distributed work environment.

What are some common challenges faced by remote python trading developers, and how can they be addressed?

Remote Python trading developers often encounter challenges such as managing effective communication with distributed teams, ensuring code reliability in automated trading systems, and keeping up with rapidly evolving market requirements. To address these, it’s important to establish clear communication channels (such as daily stand-ups or regular check-ins), write well-documented and thoroughly tested code, and stay updated on current trading technologies and market regulations. Additionally, leveraging collaborative tools like version control systems and implementing robust monitoring for trading algorithms helps ensure both team alignment and system stability.
What are popular job titles related to Remote Python Trading jobs in Florida? For Remote Python Trading jobs in Florida, the most frequently searched job titles are:
What job categories do people searching Remote Python Trading jobs in Florida look for? The top searched job categories for Remote Python Trading jobs in Florida are:
What cities in Florida are hiring for Remote Python Trading jobs? Cities in Florida with the most Remote Python Trading job openings:
Remote Python Trading jobs near you

SENIOR COMPUTER VISION ENGINEER - REMOTE SENSING VACANCY - Satlantis

SATLANTIS

Gainesville, FL • On-site, Remote

$94K - $130K/yr

Full-time

Re-posted 27 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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