Job Title

Location: Remote (CET working hours)Who we areAt Jaipur Robotics, we build AI systems that turn visual and sensor data into automation, efficiency, and operational intelligence for the waste industry. We are a fast-growing, VC-backed clean-tech startup based in Switzerland, working with leading operators across Europe and expanding our engineering team to develop industrial perception and automation systems.What we offerWe’re hiring a Senior MLOps Engineer (GCP / Computer Vision & ML Pipelines) to design and operate the infrastructure behind our ML systems. This role focuses on productionizing computer vision and perception pipelines at scale on GCP. You will work across CI/CD, cloud infrastructure, and data pipelines, ensuring models and data systems run reliably at scale.Own ML infrastructure on GCP across multiple production deploymentsBuild and operate end-to-end ML training/inference pipelines Work directly with founders and R&D engineers on core systemsContribute to scaling real-world AI systems used in industrial environmentsCompetitive salary and stock optionsKey ResponsibilitiesMLOps & CI/CD Build and maintain CI/CD pipelines using GitHub ActionsAutomate model training, validation, and deployment workflowsManage versioning of models, datasets, and pipelinesImplement safe deployment strategies (rollbacks, staged releases)Cloud / Data PipelinesDeploy and manage services on Cloud Run, GCS, Pub/Sub, and data storage systems (SQL / NoSQL / Redis)Build scalable pipelines using Apache Beam / DataflowProcess large-scale image and sensor datasetsEnsure reliability through monitoring, observability, and cost-aware designContainerization, Kubernetes & RuntimeBuild and manage Docker-based services for ML and data pipelinesDeploy and manage workloads on Google Kubernetes Engine (GKE)Optimize containers for performance, resource efficiency, and reliabilityImplement rolling deployments, health checks, and failover strategiesMaintain reproducible environments across dev, staging, and prodML Systems & CollaborationWork closely with ML engineers to productionize modelsOptimize inference pipelines and resource utilizationImplement monitoring for model performance and driftRequirementsStrong experience with GCP (Cloud Run, GKE, GCS, Pub/Sub, IAM)Experience building CI/CD pipelines (GitHub Actions or similar)Experience with Docker and Kubernetes (GKE) in productionExperience building data pipelines (Apache Beam / Dataflow)Solid understanding of ML lifecycle Familiarity with streaming pipelines and real-time systemsExperience operating in production with failure handling and debuggingStrong programming skills in PythonNice to HaveExperience working in an early-stage startup / scale-up (Experience with camera and LiDAR systemsExperience deploying on edge in restricted IT/OT industrial environmentsMaintain infrastructure using Terraform (infrastructure-as-code)Apply nowUse the contact form on or send us an email at