AI & Optimization Engineer

. Define and lead the AI strategy for MOS & MDK with a focus on operational efficiency and measurable business outcomes.

Posted 4/6/2026full-timeRemote • 🇧🇷 BrazilMid-LevelSeniorWebsite

Tools & technologies

DockerJavaScriptNode.jsPythonPyTorchScikit-LearnTensorflowTypeScript

Key responsibilities & impact

Define and lead the AI strategy for MOS & MDK with a focus on operational efficiency and measurable business outcomes.
Translate operational challenges into data and optimization problems that AI models can solve.
Establish best-practice frameworks for scalable, production-ready AI systems.
Design a standardized data baseline/schema for all mining-site telemetry and events.
Ensure data is structured, normalized, labelled and accessible for AI/ML use cases.
Work with backend engineers to evolve the data pipeline and integration standards.
Build and deploy ML/AI and optimization models such as performance optimization, anomaly detection, predictive failure & maintenance, energy-efficiency insights, operational automation recommendations.
Continuously evaluate and improve model performance in production.
Work with MOS & MDK engineering teams to embed AI models into platform workflows and APIs.
Collaborate with site-operations teams to validate results and gather feedback.
Document systems, architecture, and modelling assumptions clearly.
Promote a data-driven, efficiency-first culture within the Mining Software team.

What you’ll need

Bachelor’s or Master’s degree in Computer Science, Data Science, Applied Mathematics, Engineering, Statistics, or similar.
3+ years’ experience in AI/ML, data science, or applied optimization roles.
Proven experience designing data models / schemas / baselines for large-scale, time-series–heavy datasets.
Strong proficiency in Python and modern ML frameworks (e.g., PyTorch, TensorFlow, Scikit-Learn).
Strong JavaScript / TypeScript proficiency (Node.js ecosystem)
Familiarity with containerized workloads (Docker)
Experience developing and deploying time-series, anomaly detection, classification, and predictive models for mechanical, electromechanical, or hardware-intensive equipment/systems in production environments.
Solid understanding of signal processing and feature extraction for sensor data (e.g., electrical, thermal, vibration, or telemetry signals).
Solid understanding of optimization techniques (linear/non-linear programming, simulation, decision systems, etc.).
Experience deploying, monitoring, maintaining AI models into production systems including handling model drift and evolving operating conditions.
Excellent English communication skills and ability to collaborate in distributed teams.

Comp & perks

ATS Keywords

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Hard Skills & Tools

AI strategydata modelingmachine learningPythonPyTorchTensorFlowScikit-LearnJavaScriptTypeScriptoptimization techniques

Soft Skills

collaborationcommunicationleadershipproblem-solvingdocumentationdata-driven mindsetfeedback gatheringoperational efficiencyteamworkadaptability

Certifications

Bachelor’s degreeMaster’s degree