Machine Learning Engineer
Solve problems that only make sense once you understand how transport operations actually work.
The Role
As a Machine Learning Engineer at Fospertise, you won't be building models in a vacuum - you'll be solving problems that only make sense once you understand how transport operations actually work: why a route optimisation model needs to account for driver shift rules, why a predictive maintenance model has to work with sparse, noisy sensor data, why a demand forecast needs to hold up during a public holiday no dataset labelled as unusual.
You'll build production-grade data pipelines from real operational sources - GPS, telematics, booking systems - and work directly with domain specialists to ground your models in operational reality, not just clean benchmark data.
What You'll Do
- Design, build, and deploy ML models for route optimisation, predictive maintenance, demand forecasting, and anomaly detection
- Build robust, production-grade data pipelines from real operational sources - GPS, telematics, booking systems
- Collaborate with domain specialists to ground models in real operational constraints and edge cases
- Deploy and monitor ML systems in production, ensuring reliability at enterprise scale
- Continuously evaluate and improve model performance against real business outcomes, not just offline metrics
- Communicate model behaviour and findings clearly to both technical and non-technical stakeholders
What We're Looking For
Must-Haves
- 4+ years of experience building and deploying ML models in production environments
- Strong Python skills and experience with ML frameworks (TensorFlow, PyTorch, or scikit-learn)
- Experience with data pipeline engineering (Airflow, Spark, or equivalent)
- Understanding of MLOps practices - model versioning, monitoring, and CI/CD for ML
- Strong grasp of statistics and applied ML methods, particularly forecasting, optimisation, and anomaly detection
- Ability to translate ambiguous, real-world business problems into well-scoped ML solutions
Nice to Have
- Experience with time-series forecasting, route optimisation, or predictive maintenance
- Experience in transport, logistics, or IoT/telematics domains
- Cloud ML platform experience (AWS SageMaker, GCP Vertex AI, or Azure ML)
Why Join Fospertise
Work on Systems That Matter
You won't be building another internal tool. You'll be building the AI, real-time tracking, and cloud infrastructure that keeps buses running, fleets moving, and vehicles connected - where downtime is never just a technical problem.
Intelligence-Led Engineering
We invest in understanding the operational problem before we write code. You'll work alongside domain specialists who understand transport and automotive from the inside, not just product managers relaying requirements.
Complexity as Advantage
We take on the integrations, edge cases, and legacy systems that most teams avoid. It's the kind of work that sharpens engineers rather than wearing them down.
A Global, High-Calibre Team
Join engineers and domain specialists from leading universities across Asia and Europe, united by one mission - solving the hardest operational problems in transport and automotive.
Remote-First, Outcome-Focused
We hire for capability and hold ourselves accountable to outcomes, not hours logged. Work from wherever you do your best work.
End-to-End Ownership
From strategy through build, deployment, and 24/7 support, you'll see your work running in production - inside mission-critical operations, not shelved after handoff.
Frequently Asked Questions
Is this role fully remote?
Yes. This is a remote, full-time position, with overlap expected for team collaboration.
Do I need transport industry experience to apply?
No - it's a strong plus, not a prerequisite. We pair ML engineers directly with domain specialists so models are grounded in real operational knowledge from day one.
What does the interview process look like?
A technical screening conversation, a practical modelling or case-study exercise, and a final conversation with the engineering team.
Ready to Build Technology That Moves the World?
If you want your engineering to mean something beyond the codebase - to run inside the systems that keep fleets moving, vehicles connected, and operations live 24/7 - we want to hear from you.
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