Data and Al Infra Engineer

Oxus Metals AI; Hong Kong; Presencial; HKD 600 000 - 900 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Stock options

Competitive cash compensation

Resumo da oferta

Oxus Metals AI is seeking an experienced Cloud Engineer to own the AWS-powered cloud platform from the ground up, enabling ML engineers and geologists alike.

You will build secure, resilient infrastructure for data assets, design robust environments with cost-efficient patterns, and implement a full security control framework, to accelerate mineral discovery with AI. This role favors candidates with strong AWS expertise and a track record in startup environments.

Qualificações

• Master's degree or above in Computer Science or relevant STEM subjects.
• 3+ years as Cloud Engineer/SRE/DBA/Infra with end-to-end cloud delivery.
• Strong AWS services expertise: EC2, S3, EKS, RDS, Lambda, VPC, IAM, CloudWatch; SysOps/DevOps/SAA certs preferred.
• Solid fundamentals in relational and NoSQL databases; capable of large data storage/versioning.
• IaC tooling (Terraform, Ansible) and container orchestration (Docker, Kubernetes/EKS).
• Python or Bash scripting; Linux troubleshooting and performance tuning.
• Experience in Data & AI Infrastructure in mineral/oil & gas or geology domains preferred.
• Track record of building Data & AI Infrastructure at startups with cost-reduction results.

Responsabilidades

• Own end-to-end development of our AWS-powered cloud platform from the ground up.
• Deliver secure, resilient infrastructure for all data assets.
• Build standardized, robust computing environments for ML models and algorithms while balancing cloud cost efficiency.
• Design and implement the full security control framework.

Conhecimentos

AWS Expertise

Terraform / IaC

Docker

Kubernetes

Python

Linux

Security & Encryption

Data & AI Infra

Cloud Cost Optimization

Relational/NoSQL DBs

Formação académica

Master's degree in CS or related STEM

Ferramentas

AWS

Descrição da oferta de emprego

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