SpAItial is pioneering the development of a frontier 3D foundation model, pushing the boundaries of AI, computer vision, and spatial computing. Our mission is to redefine how industries, from robotics and AR/VR to gaming and movies, generate and interact with 3D content.
We’re looking for individuals who are bold, innovative, and driven by a passion for pushing the boundaries of what’s possible. You should thrive in an environment where creativity meets challenge and be fearless in tackling complex problems. Our team is built on a foundation of dedication and a shared commitment to excellence, so we value people who take immense pride in their work and place the collective goals of the team above personal ambition. As a part of our startup, you’ll be at the forefront of the AI revolution in 3D technology, and we want you to be excited about shaping the future of this dynamic field. If you’re ready to make an impact, embrace the unknown, and collaborate with a talented group of visionaries, we want to hear from you.
Responsibilities
Create and maintain ML and cloud infra for nascent AI company.
Design and Deploy Infrastructure: Develop and maintain scalable, high-performance cloud-based infrastructure for ML workloads and serving ML APIs or client endpoints.
Cloud Platforms: Deploy, manage, and optimize cloud-based infrastructure (AWS, Azure, GCP). Setup ML nodes for local development and distributed training workloads, maintain compatibility between the two.
System Management: Install, configure, and monitor servers.
Storage management: Optimize various types of shared / local storage maintaining big data for ML workloads.
Containerization and Orchestration: Manage and scale containerized applications using Docker, Kubernetes, Terraform, etc.
Collaboration: Work closely with the rest of the technical team to ensure smooth orchestration of the ML and production workloads.
Incident Response: Respond to cloud / production incidents, perform analysis, and implement solutions to prevent recurrence.
Key Qualifications: 3 years professional experience in a cloud-related role, preferred ML-related.
Proficiency in writing scripts (Bash, PowerShell, Python, …) to automate tasks.
Proficiency in cloud platforms (e.g., AWS, GCP, Azure).
Proficiency in containerization (e.g., Docker, Kubernetes).
Proficiency in orchestrating a cloud.
Preferred Qualifications Familiarity with Python (Jupyter) and ML frameworks (PyTorch).
Familiarity with cloud monitoring tools (e.g., Prometheus, Grafana).
Familiarity with cloud-based database systems (Amazon RDS, Aurora, Redshift, Google Cloud SQL, Spanner, …) and data-visualisation tools (Amazon QuickSight, Apache Superset).
Familiarity with CI/CD tools (e.g., CircleCI).
At SpAItial, we are committed to creating a diverse and inclusive workplace. We welcome applications from people of all backgrounds, experiences, and perspectives. We are an equal opportunity employer and ensure all candidates are treated fairly throughout the recruitment process.
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Design and Deploy Infrastructure: Develop and maintain scalable, high-performance cloud-based infrastructure for ML workloads and serving ML APIs or client endpoints.
Cloud Platforms: Deploy, manage, and optimize cloud-based infrastructure (AWS, Azure, GCP). Setup ML nodes for local development and distributed training workloads, maintain compatibility between the two.
System Management: Install, configure, and monitor servers.
Storage management: Optimize various types of shared / local storage maintaining big data for ML workloads.
Containerization and Orchestration: Manage and scale containerized applications using Docker, Kubernetes, Terraform, etc.
Collaboration: Work closely with the rest of the technical team to ensure smooth orchestration of the ML and production workloads.
Incident Response: Respond to cloud / production incidents, perform analysis, and implement solutions to prevent recurrence.
Key Qualifications: 3 years professional experience in a cloud-related role, preferred ML-related.
Proficiency in writing scripts (Bash, PowerShell, Python, …) to automate tasks.
Proficiency in cloud platforms (e.g., AWS, GCP, Azure).
Proficiency in containerization (e.g., Docker, Kubernetes).
Proficiency in orchestrating a cloud.
Preferred Qualifications Familiarity with Python (Jupyter) and ML frameworks (PyTorch).
Familiarity with cloud monitoring tools (e.g., Prometheus, Grafana).
Familiarity with cloud-based database systems (Amazon RDS, Aurora, Redshift, Google Cloud SQL, Spanner, …) and data-visualisation tools (Amazon QuickSight, Apache Superset).
Familiarity with CI/CD tools (e.g., CircleCI).
At SpAItial, we are committed to creating a diverse and inclusive workplace. We welcome applications from people of all backgrounds, experiences, and perspectives. We are an equal opportunity employer and ensure all candidates are treated fairly throughout the recruitment process.
#J-18808-Ljbffr
