Tether.to

Artificial Intelligence

• 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.

AI & Optimization Engineer

• 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.
• Collaborate with MOS & MDK engineering teams to embed AI models into platform workflows and APIs.
• Promote a data-driven, efficiency-first culture within the Mining Software team.
• Stay updated on AI, optimization and industrial analytics trends.

• 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.

• 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.

• 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.

• 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.

• 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.

• 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.

• 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.

• 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
• Promote a data-driven, efficiency-first culture within the Mining Software team.

• 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

Machine Learning Engineer

• Develop and evaluate scalable deep learning algorithms that are central to our brain decoding initiatives.
• Collaborate closely with data scientists to pioneer research in generative modeling and representation learning.
• Identify bottlenecks in data processing pipelines and devise effective solutions, improving performance and reliability.
• Maintain high standards of code quality, organization, and automatization across all projects.
• Adapt machine learning and neural network algorithms to optimize performance in various computing environments, including distributed clusters and GPUs.
• Write and revise papers, communicate and disseminate results.

Machine Learning Engineer Intern

Manager

• Lead the implementation journey of tokenization projects based on Hadron for institutional clients
• Act as the primary technical and business point of contact throughout onboarding and early operations
• Ensure a seamless transition from contract signature through the first production token issuance
• Maintain alignment across stakeholders, coordinating execution across internal teams and external partners
• Guide clients through API documentation and sandbox testing
• Diagnose and troubleshoot client integration issues
• Track onboarding progress, milestones, and dependencies
• Prepare clients for production launch and conduct monitoring after launch
• Proactively communicate timelines, blockers, and dependencies; support transition clients to self-service

AI & Optimization Engineer

AI & Optimization Engineer

AI & Optimization Engineer

AI & Optimization Engineer

AI & Optimization Engineer

AI & Optimization Engineer

AI & Optimization Engineer

AI & Optimization Engineer

AI & Optimization Engineer

AI & Optimization Engineer

AI & Optimization Engineer

Machine Learning Engineer Intern

Engagement Manager