11 months ago
Responsibilities
- Architect and operate distributed Linux-based systems across edge and cloud environments.
- Design scalable pipelines for streaming, storing, and processing large volumes of video and sensor data.
- Build containerized services to deploy perception and inference workloads at scale.
- Develop monitoring, logging, and alerting systems across edge nodes and cloud infrastructure.
- Optimize queue-based video ingestion, transcoding, and upload pipelines for reliability in bandwidth-constrained environments.
- Implement highly available infrastructure for real-time alerting, APIs, and customer-facing event systems.
- Collaborate with hardware, perception, and application teams to support rapid iteration and scale.
Requirements
- Deep experience with databases, storage, and caching technologies such as PostgreSQL, Redis, S3, and distributed file systems.
- Expertise building and maintaining real-time streaming and event systems such as WebRTC, WebSockets, and Kafka.
- Strong experience designing and securing cloud infrastructure using AWS, GCP, or Azure.
- Hands-on experience with Terraform, Ansible, and Kubernetes.
- Strong knowledge of distributed systems principles including replication, consensus, partition tolerance, and fault recovery.
- Familiarity with video pipelines, transcoding, and formats is a plus.
- Prior experience scaling edge-to-cloud systems or operating at the infrastructure layer of robotics and IoT is a bonus.
Tech Stack
About Specter
Specter delivers real-time data and insights on private companies, enabling investors to make informed, confident decisions. Harness the power of live data and AI-driven analysis to outsmart the competition and make confident decisions in private markets.