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Computer Science Remote Internships Jobs in Gainesville, FL

Anthropocene Alliance

Fall Communications Intern

Micanopy, FL · On-site +1

$13 - $17.25/hr

Interns will gain hands-on experience in grassroots communications, storytelling, digital outreach ... Flexible schedule with remote work options Key Responsibilities: * Assist in planning, writing, and ...

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Computer Science Remote Internships information

Which internship is best for a computer science student?

The best internship for a computer science student depends on their interests and career goals, but generally, internships that offer hands-on experience in software development, data structures, algorithms, or machine learning are highly valuable. Look for opportunities that provide mentorship, real-world projects, and exposure to tools like Git, Python, or Java, often with flexible remote options. Selecting an internship aligned with your desired specialization can enhance skills and improve job prospects after graduation.

What types of projects can I expect to work on during a remote computer science internship, and how will I collaborate with my team?

As a remote computer science intern, you'll typically work on real-world software development projects such as coding new application features, debugging existing code, or contributing to open-source initiatives. Communication and collaboration usually take place through tools like Slack, GitHub, and video conferencing platforms, allowing you to participate in daily stand-ups, code reviews, and team meetings. You may be paired with a mentor or work within a small agile team, gaining exposure to industry-standard development practices and collaborative workflows. While managing your own tasks independently is important, you'll also have regular check-ins and opportunities to ask questions, ensuring you remain connected and supported throughout the internship.

What is the difference between Computer Science Remote Internships vs Software Developer Internships?

AspectComputer Science Remote InternshipsSoftware Developer Internships
Required CredentialsTypically a computer science student or related field, some coding knowledgeSimilar, often requiring programming skills and coursework in software development
Work EnvironmentRemote, flexible, project-basedRemote or hybrid, focused on coding and software projects
Employer & Industry UsageTech companies, startups, research institutionsTech firms, software companies, startups
Search & Comparison IntentLooking for general computer science internship opportunitiesSeeking specific software development internship roles

Computer Science Remote Internships and Software Developer Internships share similar credentials and work environments, often targeting tech companies and startups. However, CS internships tend to be broader, encompassing various computer science topics, while Software Developer Internships focus specifically on coding and software creation. Both are valuable for gaining industry experience remotely.

What are the key skills and qualifications needed to thrive as a computer science remote intern, and why are they important?

To thrive as a Computer Science Remote Intern, you typically need a solid understanding of programming fundamentals, algorithms, and data structures, often supported by ongoing or completed coursework in computer science or related fields. Familiarity with version control systems like Git, collaboration tools such as Slack or Zoom, and exposure to languages like Python, Java, or JavaScript are highly valuable. Strong self-motivation, time management, and effective written communication skills help interns excel in remote environments. These abilities enable interns to contribute effectively to distributed teams, manage projects independently, and adapt to rapidly changing technical tasks.

What are computer science remote internships?

Computer science remote internships are work opportunities for students or recent graduates to gain practical experience in computer science while working from a location outside of a traditional office, typically from home. Interns collaborate with teams online, using digital tools to complete tasks such as coding, software development, data analysis, or technical support. These internships provide valuable exposure to real-world projects, industry practices, and professional networking, all without the need to relocate. Remote internships are especially popular in tech fields where much of the work can be done online. They often offer flexibility in schedules and are available with companies around the world.
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Computer Science Remote Internships jobs near you

SENIOR COMPUTER VISION ENGINEER - REMOTE SENSING VACANCY - Satlantis

SATLANTIS

Gainesville, FL • On-site, Remote

$94K - $130K/yr

Full-time

Re-posted 23 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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