Tether.to

AI & Optimization Engineer

Tether.to

full-time

Posted on:

Location Type: Remote

Location: Argentina

Visit company website

Explore more

✨ AI Apply
Apply

Tech Stack

DockerJavaScriptNode.jsPythonPyTorchScikit-LearnTensorflowTypeScript

About the role

  • 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
  • Align with leadership on AI roadmap, priorities, impact tracking, and KPIs
  • Document systems, architecture, and modelling assumptions clearly
  • Promote a data-driven, efficiency-first culture within the Mining Software team
  • Stay updated on AI, optimization and industrial analytics trends.

Requirements

  • 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.
Benefits
  • Flexible working arrangements
  • Professional development opportunities
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools
AI strategydata modelingmachine learningPythonPyTorchTensorFlowScikit-LearnJavaScriptTypeScriptoptimization techniques
Soft Skills
collaborationcommunicationleadershipproblem-solvingdata-driven mindsetfeedback gatheringdocumentationefficiency-first culture
Certifications
Bachelor's degreeMaster's degree