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ABOUT THE COMPANY

A fast-growing technology company based in Portugal develops advanced online risk monitoring and management systems for critical infrastructure using satellite data. With a multidisciplinary team and trusted partnerships across Europe, the Americas, and beyond, the company delivers innovative solutions that enhance operational safety and support preventive maintenance strategies for major infrastructure operators.

ABOUT THE ROLE

Our client is seeking a Senior Machine Learning Engineer to join their Technology Development Team. In this high-impact role, you will lead the design and development of scalable ML systems powering their infrastructure risk monitoring platform. The position focuses on delivering real-world outcomes through satellite imagery, time series analysis, and predictive modeling.

If you are passionate about applying machine learning to critical infrastructure and want to be part of a dynamic, international team, we would love to hear from you!

KEY RESPONSIBILITIES

Machine Learning & Technical Leadership

Design and deploy machine learning models for time series prediction, anomaly detection, and classification of satellite-derived data.
Build robust ML pipelines (data ingestion, preprocessing, training, deployment) for monitoring vegetation risks, ground motion, and infrastructure anomalies.
Drive model evaluation, validation, and iteration with performance metrics that map to business impact.

Applied Research & Engineering

Explore and integrate cutting-edge ML techniques (e.g., transformers, GNNs, self-supervised learning) into production workflows.
Collaborate with product managers, geospatial engineers, and software developers to translate business needs into ML initiatives.
Lead experimentation and prototyping, balancing innovation speed with engineering reliability.

Cross-Team Collaboration

Mentor junior engineers and data scientists.
Act as the ML subject-matter expert in internal tech reviews, client discussions, and strategic planning.
Support integration of models into Spotlite’s SaaS platform, ensuring end-to-end delivery from model to dashboard.

MAIN REQUIREMENTS

Experienced ML Practitioner:

5+ years of experience in applied ML or data science roles, with end-to-end ownership of model lifecycle.
Proficiency in Python and ML frameworks such as PyTorch or TensorFlow.
Experience with large-scale satellite data, sensor data, or remote time series is a plus.

Builder Mindset:

Track record of deploying ML models to production in a cloud-native or SaaS environment.
Solid engineering skills in data wrangling, API development, and working with spatial or temporal data.
Comfort in rapidly prototyping and iterating on novel approaches with limited supervision.

Startup-Ready Communicator:

You thrive in ambiguity and know how to move from research to MVP to production.
You know how to communicate technical tradeoffs clearly across teams.
Strong English communication skills (written and spoken).

Nice to have

Background in Earth Observation, environmental science, or infrastructure monitoring.
Experience with NDVI, or vegetation indices.
Familiarity with edge AI or large-scale model serving.

EMPLOYMENT PACKAGE

Reports to: Head of Tech
Full-Time Position, 40 Hours a Week
Location: Virtual/Remote
Competitive salary and meal allowance
Private healthcare insurance
Generous Vacation Policy
Company equipment according to professional needs
Access to E-learning platform

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