Staff Platform Engineer, Manufacturing AI

• Infrastructure & application ownership: Design and implement scalable infrastructure architectures across on-premise (edge) and cloud environments; evolve core infrastructure platforms that support production and pre-production workflows
• Pre-production environments & validation: Build and maintain sandbox, staging, and shadow-run environments that mirror production behavior; own how systems are provisioned, isolated, tested, and validated before rollout
• Replay-based testing & safe version rollouts: Design infrastructure to support A/B playback testing of models and software versions, offline and replay-based workload testing, and shadow-mode execution prior to version switching
• Reliability engineering, fault isolation & performance determinism: Define infrastructure standards that ensure reliable, isolated systems with predictable performance under real-world workloads
• Operability & cross-team collaboration: Partner with DevOps to ensure infrastructure designs are deployable, observable, and operable; collaborate with Edge and AI teams to enable safe experimentation

• Operating system: Linux
• Backend: Python (Flask, FastAPI), TypeScript/Node.js
• Orchestration & compute: Kubernetes, on-prem bare metal, VMs
• Containers: Docker
• Monitoring, observability & logging: Prometheus, Grafana, ELK
• Cloud providers: AWS, Azure, GCP
• Databases & storage: SQL, InfluxDB, MongoDB
• Messaging & IoT: MQTT, HTTP/REST, RabbitMQ, Apache Kafka
• Edge platforms: NVIDIA Jetson, Raspberry Pi (ARM)
• GPU/acceleration: CUDA, TensorRT, ONNX, OpenVINO
• ML/DL frameworks: PyTorch, TensorFlow, Keras, scikit-learn
• Scientific computing: NumPy, Pandas
• Computer vision: OpenCV
• Cameras & vision I/O: GenICam, GigE Vision, USB3 Vision
• Industrial automation: PLC integration; protocols: Ethernet/IP, Modbus, Profinet, OPC UA

• You have significant experience supporting the design and implementation of scaled production environments in hybrid (edge-cloud) or on-prem environments
• You have strong Linux systems knowledge and experience building and operating underlying compute platforms
• You have significant experience with infrastructure orchestration platforms (Kubernetes/K8s preferred) and/or virtualization platforms
• You are experienced with monitoring, observability and alerting stacks and best practices 
• You have high comfort with, and understanding of, distributed systems and failure modes
• You have enough software engineering skills to be dangerous, and specific command of Python for infrastructure automation and validation tooling
• You have experience collaborating effectively within and across cross-functional delivery teams
• You are a contagiously curious person with entrenched learning habits

• You have experience designing and operating scaled production environments for manufacturing, robotics, IoT and/or industrial automation applications
• You have deep expertise in computer vision, robotics, or manufacturing automation
• You have experience supporting GPU-based or real-time workloads
• You are predisposed to mentorship and crafting a culture of continuous improvement
• You have experience scaling an AI and/or B2B SaaS venture

Compensation