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Machine Learning Engineer
Perth, Australia
Actively hiring, first seen by us 2 days ago- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
Full-time · Permanent — employment source
About the Role We’re looking for a Senior Machine Learning Engineer to help evolve TytonAI, our large-scale computer vision platform for ecological classification. This is a permanent full-time role initially based in our Leederville office, with a transition to be based out of SLR Consulting’s Subiaco office, next year. 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.
Employment type in the employer’s posting: Full time
From the employer’s posting
Before you apply
- Work authorization
- Must already have the right to work in Australia
Note that applicants must have valid working rights in Australia and be based in Perth or be willing to relocate
What you’ll work on
Full postingWe’re looking for a Senior Machine Learning Engineer 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.
Improve segmentation and classification models for TytonAI's computer vision platform
Design, train and deploy deep learning models for remote sensing imagery
Turn successful experiments into production systems
Cut inference time, memory use and cloud costs
Build tooling for training data, evaluation and batch inference
From the employer’s posting
We’re looking for a Senior Machine Learning Engineer to help evolve TytonAI, our large-scale computer vision platform for ecological classification. This is a permanent full-time role initially based in our Leederville office, with a transition to be based out of SLR Consulting’s Subiaco office, next year.
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.
Improve TytonAI’s core computer vision capabilities (segmentation, classification, fine-tuning)
Design, train, and deploy deep learning models for large-scale remote sensing and geospatial classification
Translate research ideas into production systems
Identify performance bottlenecks and improve inference speed, memory usage, and cloud efficiency
Build tooling for training data, evaluation, and batch inference
What you’ll bring
All qualificationsCore experience
- Strong PyTorch and Python engineering skills
- Solid grasp of training, evaluation, deployment and optimisation
- Experience maintaining or extending existing ML codebases
- Valid working rights in Australia; based in Perth or willing to relocate
Qualification wording
Strong PyTorch and Python engineering skills.
Solid understanding of training, evaluation, deployment, and optimisation
Experience maintaining or extending existing ML codebases
applicants must have valid working rights in Australia and be based in Perth or be willing to relocate
About Slrconsulting
Tyton Ecological Intelligence (Tyton) builds AI-first platforms for ecological monitoring at landscape scale.
In the employer’s words · Read in context
Posting record
Report an errorActively hiringFirst seen by us 2 days ago, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Nov 2, 20262 days ago
- Recorded sightings
- 3
- Last seen by us
- Nov 4, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Slrconsulting is hiring
2 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Hiring recordSee how this role fits your experience
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- Python
- GCP
- PyTorch
Where the posting names them
- 3+ years experience in Machine Learning with Computer Vision. - Strong PyTorch and Python engineering skills. - Solid understanding of training, evaluation, deployment, and optimisation
- Build tooling for training data, evaluation, and batch inference - Work within cloud environments (primarily Google Cloud) and Linux environments - Maintain documentation and engineering standards
- MLOps experience (CI/CD for ML, model monitoring, reproducibility) - Cloud computing experience, GCP preferred. Our Benefits
Your next step
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About the role
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
US government figures for computer and information research scientists
- Median yearly pay, May 2025
- $140,300
- Expected change, 2025 to 2035
- 21.8% more jobsagainst 3.5% for all jobs
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Job description
About the Business
Tyton Ecological Intelligence (Tyton) builds AI-first platforms for ecological monitoring at landscape scale.
Our products, TytonAI and TytonIQ, combine machine learning, high-resolution aerial imagery (drone, aircraft and 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 that enables ecologists and environmental teams to replace manual workflows with repeatable, ML-driven processes. TytonAI is already deployed across major mining operations in Western Australia, and we’re now expanding this capability for broader global use.
Our recent acquisition by SLR Consulting provides us with a global platform, driving us into an exciting period of growth. Learn more about Tyton and our technology at http://www.tytonei.com
About the Role
We’re looking for a Senior Machine Learning Engineer to help evolve TytonAI, our large-scale computer vision platform for ecological classification. This is a permanent full-time role initially based in our Leederville office, with a transition to be based out of SLR Consulting’s Subiaco office, next year.
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. This role suits someone who enjoys shipping real ML products - not just building prototypes.
Key Responsibilties
- Improve TytonAI’s core computer vision capabilities (segmentation, classification, fine-tuning)
- Ideate, design, and run experiments focused on customer impact
- Design, train, and deploy deep learning models for large-scale remote sensing and geospatial classification
- Explore emerging ML techniques
- Translate research ideas into production systems
- 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
- Work within cloud environments (primarily Google Cloud) and Linux environments
- Maintain documentation and engineering standards
Skills and Experience
- 3+ years experience in Machine Learning with Computer Vision.
- Strong PyTorch and Python engineering skills.
- Solid understanding of training, evaluation, deployment, and optimisation
- Experience maintaining or extending existing ML codebases
- Strong problem-solving ability with real-world data
- Note that applicants must have valid working rights in Australia and be based in Perth or be willing to relocate.
Desirable
- Geospatial / remote sensing experience.
- Exposure to Ecology
- Experience working with large GIS imagery datasets (satellite, drone, aerial)
- MLOps experience (CI/CD for ML, model monitoring, reproducibility)
- Cloud computing experience, GCP preferred.
Our Benefits
- A technical role with meaningful ownership of core ML systems
- Fast innovation cycle from idea → experiment → production
- Real-world ML problems at meaningful scale
- Competitive salary + flexible hybrid work
- Small, high-calibre team with real product influence
- Perth-based, practical, focused, low-ego culture
Next Steps
The problems here are genuinely interesting. You'll be working on proprietary ML infrastructure applied to real ecological data, in a domain where the technical challenges and the environmental stakes are both real. The team is small and experienced, which means less overhead and more ownership, and our recent acquisition by SLR Consulting gives us a global platform from which to scale.
Apply with your CV if you’d like to grow alongside a business doing something that matters.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Perth, Australia
- Ideate, design, and run experiments focused on customer impact - Design, train, and deploy deep learning models for large-scale remote sensing and geospatial classification - Explore emerging ML techniques
More source context
Desirable - Geospatial / remote sensing experience. - Exposure to Ecology
More relevant text appears in the full description.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.