Cloud Engineer

About Us

At Neuracore, we're building the world's first robot learning cloud service (https://github.com/NeuracoreAI/neuracore).

Our platform eliminates the complexity of traditional robotics development by providing a complete end-to-end solution for data collection, model training, and deployment that works across different robot types and configurations.

Our multidisciplinary team is at the forefront of making robot learning accessible to organisations worldwide, from manufacturing and logistics to healthcare and research institutions. We're transforming how robotics teams develop, train, and deploy intelligent systems by providing cloud-native infrastructure that scales from small research projects to enterprise-wide robot fleets.

About the Role

We're looking for a Cloud Engineer to join our growing team and own the infrastructure backbone of our robot learning platform. In this role, you'll design and scale the cloud systems that power data ingestion from robot fleets, distributed model training, and low-latency deployment pipelines. You'll make foundational infrastructure decisions as we grow from early customers to enterprise-scale deployments.

Key Responsibilities

• Design and own the cloud architecture powering our end-to-end robotics platform — from data collection pipelines to model training and deployment
• Build and scale infrastructure for ingesting, storing, and processing large volumes of robot telemetry and sensor data
• Architect multi-cloud or cloud-native solutions (AWS/GCP/Azure) that support diverse robot types and fleet sizes
• Lead infrastructure-as-code practices using tools like Terraform or Pulumi to ensure reproducible, auditable environments
• Own and evolve CI/CD pipelines, container orchestration (Kubernetes/ECS), and deployment strategies across environments
• Collaborate with ML and backend engineers to optimize compute resource allocation for model training workloads (GPU/TPU scheduling, spot instances, etc.)
• Define observability standards — logging, metrics, alerting — across the platform
• Drive security best practices including IAM, secrets management, network policy, and compliance posture
• Mentor engineers on cloud-native patterns and participate in technical hiring

Requirements

• 5+ years of professional engineering experience, with 3+ years focused on cloud infrastructure
• Deep hands-on expertise with at least one major cloud provider (AWS, GCP, or Azure) — and familiarity with the others
• Strong experience with infrastructure-as-code (Terraform, Pulumi, or CDK)
• Proven ability to design and operate distributed systems at scale — queuing, event streaming, storage, networking
• Experience with container orchestration (Kubernetes preferred) and modern deployment patterns
• Solid understanding of networking fundamentals: VPCs, load balancing, DNS, TLS, service meshes
• Experience building data pipelines for high-throughput or time-series workloads
• Strong CI/CD background — pipeline design, automated testing, environment promotion strategies
• Excellent communication skills; comfortable making and documenting architectural trade-offs
• (Preferred) Experience supporting ML training infrastructure — GPU clusters, distributed training, model registries
• (Preferred) Background in robotics, edge computing, or IoT data systems
• (Preferred) Startup or high-growth environment experience