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Lead end-to-end program management for mining initiatives in Central America, coordinating multidisciplinary teams, permitting, stakeholder and government engagement, budgets, risk mitigation, governance, KPIs, and ensuring regulatory, HSE, and ESG compliance across multiple interrelated exploration and development projects.

Lead end-to-end program management for mining initiatives in Central America, coordinating exploration, permitting, technical studies, and operational readiness. Define scope, budgets, milestones and KPIs; manage multidisciplinary teams, vendors, and government/community relationships; monitor risks and compliance with regulations, HSE and international mining standards; produce executive reporting and drive program delivery.

Research and engineering of vision-language multimodal models across the full lifecycle: data curation, training, fine-tuning (including RLHF and distillation), evaluation, efficiency optimization, distributed GPU training, and publishing research. Drive deployable, resource‑efficient models and production-ready training workflows.

Lead end-to-end program management for mining initiatives in Central America, coordinating exploration, permitting, technical studies, operations readiness, stakeholders, and regulators. Define scope, budgets, milestones, and governance; manage multidisciplinary teams and external consultants; oversee budgets, CAPEX tracking, vendor management, HSE compliance, risk mitigation, KPI reporting, and executive updates.

Drive end-to-end research and engineering on vision-language and multimodal models: data curation, training pipelines, post-training workflows (fine-tuning, distillation, RLHF), efficiency and deployment optimizations, distributed GPU training, evaluation frameworks, and publishing research.

Support daily operations of a multi-asset investment and treasury platform: manage trade confirmations, settlements, reconciliations, wallet/custodian workflows, resolve breaks, maintain controls, produce reporting, support audits, and build automation and operational documentation.

As an AI Research Engineer, you will focus on model compression techniques to enhance performance of AI systems, ensuring efficient deployment on edge devices while maintaining accuracy.

Drive innovation in post-training methodologies for AI models, focusing on agentic behaviors, tool use, and enhancing model capabilities for real-world applications.

Drive innovation in model compression and efficient deployment for multimodal AI systems. Focus on reducing model footprint and enhancing performance on resource-constrained edge devices.

The AI Research Engineer will innovate in model compression for multimodal AI systems, focusing on reducing model size and computational cost while ensuring high performance across edge devices.