SkyBound is building cutting‑edge technology at the intersection of AI, machine learning and autonomous aerial systems. We’re an ambitious, forward‑thinking team developing the intelligent software that powers next‑generation unmanned aviation.
If you’re excited by real‑world innovation, curious problem‑solving and the chance to work on technology that genuinely pushes boundaries, SkyBound is a place where you can grow quickly and make meaningful impact. Join us as we shape the future of intelligent aerial systems.
Role Summary
We’re looking for an enthusiastic and motivated Junior ML/AI Researcher to join our growing Data and AI team, supporting the development of intelligent drone systems and computer vision applications.
This is an excellent opportunity for a recent graduate or early‑career professional to gain hands‑on experience across the full AI development lifecycle — from data preprocessing and annotation to model deployment and testing.
Working alongside our Senior ML/AI Researcher and 3D Simulation Engineer, you’ll contribute to cutting‑edge projects while developing expertise in computer vision, synthetic data workflows and AI system integration. This is a hands‑on learning role within a lean, high‑impact team based in Southampton (remote‑first, with monthly office collaboration).
Key Responsibilities
* Build and maintain automated data ingestion pipelines for RGB and thermal imaging datasets.
* Develop preprocessing workflows including augmentation, normalisation and format conversion.
* Maintain data‑cataloguing systems for versions, annotations and metadata.
Annotation & Dataset Management
* Design and implement annotation workflows for object detection and tracking.
* Coordinate with annotation teams and develop tools to streamline labelling.
* Validate annotation quality and ensure consistency across datasets.
* Manage integration of synthetic and real‑world datasets, ensuring correct splits.
* Assist with model‑training experiments, tuning and evaluation.
* Implement baseline models and benchmark comparisons.
* Develop automated testing frameworks for validation and regression testing.
* Support deployment pipelines and simulation‑environment integration.
Tooling & Infrastructure
* Build internal tools and dashboards for visualisation, monitoring and experiment tracking.
* Implement automated reporting for model performance and data quality.
* Support MLOps infrastructure including experiment management and versioning.
* Develop integration scripts between simulation outputs and ML pipelines.
Testing & Validation
* Design and run testing protocols in simulated and real‑world scenarios.
* Support SITL/HITL testing frameworks for perception validation.
* Contribute to benchmarking and comparative analysis.
* Assist in creating test datasets and evaluation metrics.
Required Skills & Experience
* Recent graduate or 0–2 years’ experience in CS, data science, ML or related fields.
* Strong Python skills; familiarity with pandas, numpy and basic ML frameworks.
* Understanding of computer‑vision fundamentals and image‑processing concepts.
* Experience working with large datasets and data‑handling workflows.
* Basic knowledge of supervised learning, evaluation metrics and ML concepts.
* Familiarity with Git and collaborative development practices.
* Strong problem‑solving skills and attention to detail.
* Academic or project experience in computer vision, object detection or classification.
* Familiarity with PyTorch or similar deep‑learning frameworks.
* Experience with cloud platforms (AWS, GCP, Azure) or containerisation (Docker).
* Understanding of software‑testing principles and automation.
* Knowledge of drones, robotics or autonomous systems.
* Experience with annotation tools (CVAT, Labelbox, etc.).
* Familiarity with thermal or multispectral imaging.
* Understanding of MLOps concepts and model‑deployment workflows.
* Experience with data‑visualisation tools and dashboards.
* Knowledge of geospatial data and GIS concepts.
* Mentorship from senior team members with regular code reviews.
* Exposure to cutting‑edge AI research and real‑world drone autonomy.
* Collaboration with simulation engineers and ML researchers.
* Support for conferences and professional development.
* Opportunities to contribute to research publications and technical presentations.
Location & Working Pattern
Hybrid:
Remote‑first with one day per month in our Southampton office.
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