Position Overview

Build scalable infrastructure for real-time maritime intelligence platform processing 40B+ AIS messages and 10TB+ satellite imagery monthly. Deploy ML inference pipelines, geospatial databases, and React frontend to handle enterprise maritime customers globally.

Responsibilities
Deploy AIS Analytics pipelines.
Architect PostGIS + TimescaleDB for 100M+ vessel position records.
Implement CI/CD for React frontend, Python ML backend, and Docker containers.
Build real-time streaming pipelines (AIS + CV detections frontend).
Local monitoring (Prometheus/Grafana), secure air-gapped configs.
Monitor system performance: <100ms vessel track queries, 99.9% uptime.

Requirements
3+ years Kubernetes (EKS/GKE/AKS) with autoscaling and multi-availability zones.
Docker containerization for ML models, geospatial services,



React apps- PostgreSQL/PostGIS optimization for geospatial workloads (GIST indexes, partitioning).
GPU infrastructure: NVIDIA Docker, TensorRT, Triton Inference Server.
CI/CD: Bitbucket/Gitlab/Github.
Cloud platforms: AWS/GCP (SageMaker, ECS, RDS, EKS).

Preferred Experience
Geospatial workload optimization (PostGIS, GeoServer, Tile38).
ML model deployment at scale (Triton, KServe, Seldon Core).
Real-time geospatial streaming (Kafka, Redis Geo, NATS).

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

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