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SkyFi

Senior Computer Vision Research Engineer

Posted Yesterday
Remote
Hiring Remotely in United States
180K-230K Annually
Senior level
Remote
Hiring Remotely in United States
180K-230K Annually
Senior level
The role involves developing geospatial computer vision analytics, managing projects from research and design to production while collaborating with cross-functional teams.
The summary above was generated by AI
Title

Senior (or Mid) Computer Vision Research

Location

While our headquarters is located in Austin, TX, we are a remote team and this role is available anywhere in the United States.

Our Mission

We’re unlocking the secrets of our planet. SkyFi simplifies obtaining high-resolution Earth observation data and analytics, ensuring businesses and professionals a seamless and efficient user experience. No more complex procedures or hefty price tags. We’re empowering everyone, from individuals to companies, to understand and utilize the power of space for good.

What we do has tremendous potential to solve meaningful problems in our world. This technology is a powerful tool for enterprises and individuals, enabling them to leverage satellite imagery and analytics for critical applications: assessing the structural integrity of bridges to prevent failures, monitoring crop health for optimized agricultural output, tracking endangered species for environmental conservation, and exploring a myriad of other innovative use cases yet to be discovered. Grab the chance to be part of this. Join a team of open-minded, dynamic people solving new challenges and working on new technology in an exciting market with immense growth. SkyFi is the place for you.

The Job

As a Senior (or Mid) Computer Vision Research Engineer on the AI/Advanced Engineering team, you’ll be a core researcher driving the development of geospatial computer vision analytics on SkyFi’s platform. Working alongside other CV researchers, you’ll independently own analytics tracks, from literature review and architecture design through training, iteration, and evaluation, across a broad and growing portfolio of geospatial analytics, from object detection and segmentation to change detection, environmental monitoring, maritime domain awareness, and damage assessment, serving both commercial and government customers.

You bring rigorous experimental methodology and deep remote sensing knowledge to a team that values both disciplined research and creative problem solving. You’ll design clean experiments with proper baselines and ablations, while also proposing unconventional approaches when the problem calls for it. You’ll partner closely with our applied CV, evaluation, data platform, and ML systems engineers to ensure your research translates into production-ready analytics that help customers understand what’s happening on Earth. This is a high-ownership position where your research directly becomes the product.

What You’ll Do
  • Own one or more computer vision analytics verticals end-to-end, driving them from problem formulation and literature review through architecture design, training, and iterative improvement.

  • Design and execute rigorous experiments with proper baselines, ablations, and failure analysis to advance model quality across detection, segmentation, change detection, and anomaly detection tasks on diverse Earth observation imagery.

  • Research, adapt, and apply state-of-the-art CV techniques to geospatial problems, critically evaluating what transfers from benchmarks to real-world EO/SAR imagery and what does not.

  • Contribute to foundation model research as part of SkyFi’s broader AI roadmap, including work with modern vision transformer architectures and foundation model adaptation techniques (fine-tuning, adapter layers, prompting).

  • Partner with other CV engineers on architectural decisions, bringing a complementary perspective grounded in methodical experimentation and formal analytical rigor.

  • Collaborate with evaluation engineering to define metrics, acceptance criteria, and performance targets for your analytics, and iterate based on error analysis and failure taxonomy.

  • Work with data platform and label ops engineers to specify training data requirements, labeling strategies, and dataset compositions for new and evolving analytics.

  • Partner with ML systems engineering to hand off research outputs for production, hardening, deployment, and scaling.

  • Stay current with the rapidly evolving CV and remote sensing research landscape and bring relevant ideas back to the team.

Must Haves
  • Strong computer vision research experience in detection, segmentation, change detection, or closely adjacent domains, with demonstrated work that has been trained, evaluated, and iterated on.

  • Hands-on remote sensing / geospatial CV experience working with real Earth observation imagery (EO, and ideally multi-spectral and/or SAR), including navigating multi-sensor variation, atmospheric and seasonal effects, and noisy or partial ground truth.

  • Deep PyTorch fluency and comfort working with modern vision transformer architectures (e.g., DINO, SAM, CLIP, or similar foundation models).

  • Strong experimental methodology: you can articulate your ablation strategy, describe how you diagnose model failures, and explain how you decide when a research direction is worth pursuing versus abandoning.

  • Ability to work independently on a research track while coordinating closely with a small, fast-moving team.

  • Clear communication of uncertainty, tradeoffs, and research findings to both technical and non-technical stakeholders.

  • MS or PhD in Computer Science, Electrical Engineering, Remote Sensing, or a related field, or equivalent industry research experience.

Nice to Haves
  • Direct experience with temporal analysis or change detection on satellite imagery.

  • Experience adapting or fine-tuning large pretrained vision models for downstream geospatial tasks.

  • Publications in CV, remote sensing, or related venues (valued as a signal of research rigor, not as a strict requirement).

  • Experience with multi-modal data fusion across sensor types (e.g., EO + SAR, optical + multi-spectral) for geospatial analysis.

  • Experience with continual learning or drift monitoring strategies relevant to multi-sensor imagery pipelines.

  • Exposure to defense, intelligence community, or government geospatial workflows.

At SkyFi You Will
  • Be well compensated. Possibility for equity.

  • Receive best-in-class benefits, including premium medical, dental, and vision coverage and 20 days paid time off

  • Play a critical role in building a market-changing product in the exciting realm of Space

  • Thrive in a fast-paced, dynamic environment that rewards initiative, innovation, and getting things done

SkyFi is an equal-opportunity employer that values and encourages workplace diversity.

Salary Band: $1800,000-$230,000

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