DevOps Engineer – AI​/ML & IoT Infrastructure

At Currux Vision
, we're building the future of smart infrastructure. Our autonomous AI systems—powered by cutting-edge computer vision and machine learning—help cities, Departments of Transportation (DoTs), government agencies, and infrastructure developers monitor, optimize, and monetize complex projects. From real-time traffic analytics and incident detection to edge-to-cloud IoT synchronization, we process billions of data points daily to create safer, smarter, and more sustainable urban environments.

We're growing our team and looking for a talented Dev Ops Engineer to help with the reliability, scalability, and automation of our AI/ML pipelines and IoT-heavy deployments.

• Design, implement, and maintain robust CI/CD pipelines for AI/ML models and IoT applications using tools like Jenkins, Git Hub Actions, or similar
• Manage and optimize cloud and on-premise infrastructure across GCP, AWS, and hybrid environments
• Optimize IoT device management
  , including provisioning, monitoring, and lifecycle operations
• Collaborate closely with AI/ML engineers, software developers, and data scientists to automate deployments and integrate IoT protocols seamlessly
• Monitor system health using tools like Prometheus
  , Grafana
  , and implement disaster recovery & high-availability strategies
• Troubleshoot production issues in real-time, with a focus on IoT connectivity, data ingestion, and edge-to-cloud synchronization
• Contribute to and evolve best practices for containerization (Docker/Kubernetes) in IoT-heavy, edge-computing environments

• 2+ years of hands-on experience in Dev Ops or Site Reliability Engineering (SRE)
• Strong proficiency in scripting and automation (
  Python
  , Bash
  , and infrastructure-as-code tools)
• Solid experience with container orchestration (Kubernetes preferred) and major cloud platforms (AWS and/or GCP)
• Familiarity with monitoring, logging, and alerting systems (Prometheus, Grafana, ELK stack, etc.)
• Excellent problem-solving skills and a collaborative, team-first mindset

• Background in AI/ML deployment
  , MLOps, or computer vision applications
• Knowledge of IoT security best practices (encryption, zero-trust models, secure boot, etc.)
• Relevant certifications such as AWS Certified Dev Ops Engineer
  , Google Cloud Professional Dev Ops Engineer
  , CKAD/CKA, or similar

• Work on mission-critical AI systems deployed across U.S. cities and DOTs
• Solve real-world problems in traffic safety, congestion reduction, and sustainable infrastructure
• Be part of a small, high-impact team (11-50 people) driving innovation in AI for public good

If you're passionate about reliable infrastructure that powers autonomous AI at scale—especially at the intersection of cloud, edge, IoT, and computer vision— we'd love to hear from you!

Currux Vision – Autonomous AI Systems for Smarter Infrastructure