Data and Al Infra Engineer

Il y a 4 jours

Brussels, Brussels-Capital, Belgique Oxus Metals AI Temps plein
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.

We offer
competitive cash compensation plus stock options. Qualifications Master'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