Data and AI Infra Engineer

Company Description Oxus Metals AI is a AI native company dedicated to advancing data and artificial intelligence solutions for critical mineral discovery. Our headquarter is in Singapore with global operation. We aim to fill the multi-trillion $ critical mineral supply gap with a faster, cheaper and more efficient mineral exploration approach power by AI. Role Description As a core technical pillar of the company, you will own end-to-end development of our AWS-powered cloud computing platform from the ground up to empower our ML engineers and geology specialists. Your core objectives cover three key pillars: 1) Deliver secure, resilient foundational infrastructure for all corporate data assets; 2) build standardized, robust and secure computing environments for in-house ML models and algorithms while striking an optimal balance between computing performance and startup-focused cloud cost efficiency; 3) design and implement the full security control framework. Qualifications - Bachelor's degree or above in Computer Science or relevant STEM subjects - At least 3 years of hands-on working experience as Cloud Engineer, SRE, DBA or Infrastructure Engineer, with proven end-to-end public cloud project delivery portfolio preferred - In-depth command of core AWS services including EC2, S3, EKS, RDS, Lambda, VPC, IAM and CloudWatch; AWS SysOps / DevOps / Solutions Architect certifications preferred - Solid fundamentals in underlying database technologies, proficient in deployment and tuning of relational and NoSQL databases with practical experience managing storage and versioning for massive heterogeneous datasets - Skilled in IaC tools (Terraform, Ansible) plus container orchestration technologies (Docker, Kubernetes/EKS) - Expertise in Python or Bash scripting with proven Linux troubleshooting and system performance tuning capabilities - Well-versed in data encryption and network segmentation; capable of reproducing misconfiguration issues with limited contextual information, isolating root causes and resolving critical problems under tight deadlines - Prior Data & AI Infrastructure implementation experience within mineral, oil & gas, geological exploration or remote sensing industries with domain knowledge of geoscience dataset characteristics preferred - Track record of building Data & AI Infrastructure from zero to one at early-stage startups with measurable cloud cost reduction achievements preferred

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