Senior MLOps Engineer; GCP​/CV​/Perception Pipelines

Position: Senior MLOps Engineer (GCP / CV / Perception Pipelines)
Location:

Remote (CET working hours)
Who we are   At 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 offer   We’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 product ionizing 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  ML infrastructure on   GCP   across multiple production deployments
Build and operate   end-to-end ML training/inference pipelines
Work directly with founders and R&D engineers on core systems
Contribute to scaling real-world AI systems used in industrial environments
Competitive salary and stock options

Key Responsibilities  MLOps & CI/CD     Build and maintain CI/CD pipelines using Git Hub Actions
Automate model training, validation, and deployment workflows
Manage versioning of models, datasets, and pipelines
Implement safe deployment strategies (rollbacks, staged releases)

Cloud / Data Pipelines    Deploy and manage services on   Cloud Run, GCS, Pub/Sub, and data storage systems (SQL / No

SQL / Redis)
Build scalable pipelines using   Apache Beam / Dataflow
Process large-scale image and sensor datasets
Ensure reliability through monitoring, observability, and cost-aware design
Containerization, Kubernetes & Runtime    Build and manage Docker-based services for ML and data pipelines
Deploy and manage workloads on Google Kubernetes Engine (GKE)
Optimize containers for performance, resource efficiency, and reliability
Implement rolling deployments, health checks, and failover strategies
Maintain reproducible environments across dev, staging, and prod
ML Systems & Collaboration    Work closely with ML engineers to product ionize models
Optimize inference pipelines and resource utilization
Implement monitoring for model performance and drift

Requirements    Strong experience with GCP (Cloud Run, GKE, GCS, Pub/Sub, IAM)
Experience building CI/CD pipelines (Git Hub Actions or similar)

Experience with Docker and Kubernetes (GKE) in production
Experience building data pipelines (Apache Beam / Dataflow)
Solid understanding of ML lifecycle
Familiarity with streaming pipelines and real-time systems
Experience operating in production with failure handling and debugging
Strong programming skills in Python

Nice to Have    Experience working in an early-stage startup / scale-up (

Experience with camera and LiDAR systems
Experience deploying on edge in restricted IT/OT industrial environments
Maintain infrastructure using Terraform (infrastructure-as-code)

Apply now   Use the contact form on  or send us an email at