Senior Data Scientist

About Tyton

Tyton Ecological Intelligence builds AI-first platforms for ecological monitoring at landscape scale.

Our products, TytonAI and TytonIQ, combine machine learning, high-resolution aerial imagery (drone, aircraft, satellite), and cloud analytics to automate vegetation classification, rehabilitation monitoring, weed mapping, and biodiversity assessment across thousands of hectares.

Tyton is creating a globally scalable, enterprise platform used by ecology consultancies and environmental teams to replace manual workflows with repeatable, ML-driven processes. TytonAI is already deployed on major mining operations in Western Australia, and we’re now productising this capability for global use.

We’re a founder-led, fast-growing company focused on building world-leading AI systems that operate reliably at scale. Our engineers work on massive imagery datasets, deep learning pipelines, and real-world ML performance problems rarely found in typical SaaS environments.

The Role

We’re looking for a Senior Data Scientist to help evolve TytonAI, our large-scale computer vision platform for ecological classification.

This is a hands-on senior role combining R&D and delivery. You’ll own core ML systems end-to-end: experimenting with new ideas, turning successful models into production pipelines, and continuously improving performance, reliability, and scale.

You’ll work on deep learning for high-resolution imagery, geospatial pipelines, and cloud workflows supporting enterprise customers globally. Because the platform turns imagery into decision-grade ecological figures, the role uniquely sits at the intersection of four disciplines at once; machine learning (classical ML and deep-learning computer vision on imagery), geospatial / remote-sensing engineering, applied statistics & econometrics, and ML infrastructure. This role suits someone who enjoys shipping real ML products - not just building prototypes.

Key Responsibilities

• Own and extend TytonAI’s PyTorch-based ML codebase (production + R&D) ensuring stability, maintainability, and performance
• Design and run experiments focused on customer impact
• Design, train, and deploy deep learning models for large-scale remote sensing and geospatial classification
• Improve TytonAI’s core computer vision capabilities (segmentation, classification, fine-tuning)
• Translate research ideas into production systems
• Build and optimise pipelines for raster/vector spatial data and large-area processing
• Apply survey / spatial sampling techniques to extract representative, well-stratified tiles/sites for training and validation sets.
• Design evaluation strategies suited to imbalanced and rare classes (rare species, lifeforms), so that reported figures are genuinely trustworthy.
• Identify performance bottlenecks and improve inference speed, memory usage, and cloud efficiency
• Contribute to platform architecture and technical direction as the product scales
• Build tooling for training data, evaluation, and batch inference
• Explore emerging ML techniques, including foundation models and LLMs where relevant
• Work within cloud environments (primarily Google Cloud) and Linux environments
• Maintain documentation and engineering standards
• Mentor junior engineers

Essential Skills and Experience

• 8+ years professional experience across data science, applied statistics, machine learning and deep learning, including a proven track record shipping production ML systems
• Strong PyTorch and Python engineering skills
• Deep-learning computer vision (PyTorch) applied to high-resolution imagery ; training and fine-tuning models for semantic segmentation and pixel/object classification on satellite, aerial or drone data (i.e. modern DL-based CV, not classical-CV-only, tabular- or NLP-only ML).
• Geospatial & remote-sensing engineering: hands-on raster/vector processing, coordinate reference systems, tiling, mosaicking, spatial joins/overlays and polygon geometry — using QGIS and PostGIS.
• Strong classical machine learning alongside deep learning, feature engineering and models such as tree ensembles / gradient boosting, where they outperform or complement neural nets.
• Formal grounding in statistics, probability and econometrics, survey / spatial sampling, uncertainty quantification, controlling for confounders (effects "all else equal"), and evaluation / metric design for imbalanced or rare classes.
• End-to-end MLOps: containerised training and inference (Docker / Kubernetes), CI/CD for ML, experiment tracking, model monitoring and reproducibility.
• Experience maintaining or extending existing ML codebases
• Proven track record shipping production ML systems
• Solid understanding of model training, evaluation, deployment, and optimisation
• Linux + cloud experience (GCP preferred)
• Strong problem-solving ability with real-world data
• Demonstrated experience leading or managing a technical team (ML / statistics / data) while remaining hands-on, setting direction, mentoring, and owning delivery.
• Geospatial / remote sensing experience
• Experience working with large imagery datasets (satellite, drone, aerial)
• GIS and related tool exposure (e.g. QGIS / ArcGIS)

Note that applicants must be based in Perth

What We Offer

• A senior technical role with meaningful ownership of core ML systems
• Fast innovation cycle from idea → experiment → production
• Opportunity to build a globally scalable environmental AI platform
• Competitive salary + flexible hybrid work
• Small, high-calibre team with real product influence
• Perth-based office with a practical, focused, low-ego culture

Pay: $130,000.00 – $155,000.00 per year

Work Location: In person