Senior MLOps Engineer

Jaipur Robotics; Schweiz; Remote; CHF 120,000 - 180,000; Full time

Benefits offered by this job

Stock options

Competitive salary

Job summary

Jaipur Robotics, a Switzerland‑based clean‑tech startup, seeks a Senior MLOps Engineer to design and operate the infrastructure behind ML systems. You will focus on productionizing computer vision and perception pipelines at scale on GCP, working across CI/CD, cloud infrastructure, and data pipelines to ensure reliable models and data services.

You will collaborate with founders and R&D engineers on core systems, deploy on GKE, Cloud Run, and Dataflow, and contribute to scalable AI in industrial

Qualifications

• Proven experience building end‑to‑end ML pipelines.
• Strong knowledge of CI/CD for ML systems and data platforms.
• Hands-on with Google Cloud Platform (GCP) and cloud ML tooling.
• Familiarity with Docker, Kubernetes, and scalable data processing.

Responsibilities

• Design and operate production ML training/inference pipelines.
• Automate model training, validation, and deployment workflows.
• Manage versions of models, datasets, and pipelines.
• Collaborate with R&D to scale AI systems in industrial environments.

Skills

MLOps

CI/CD

GCP

Docker

Kubernetes

Data pipelines

Monitoring

Observability

Education

Bachelor’s degree in CS or related

MS preferred

Tools

Docker

GKE

Dataflow

SQL/NoSQL

Job description

At Jaipur Robotics, we’re building AI-powered solutions that transform the waste industry — turning complex data into automation, efficiency, and environmental impact. As a fast-growing, VC-backed clean-tech startup based in Switzerland, we work with leading waste operators across Europe and are now scaling our hardware and operations capabilities to support rapid deployment in the field.

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 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.

• 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 GitHub Actions
• Automate model training, validation, and deployment workflows
• Manage versioning of models, datasets, and pipelines
• Implement safe deployment strategies (rollbacks, staged releases)
• Deploy and manage services on Cloud Run, GCS, Pub/Sub, and data storage systems (SQL / NoSQL / Redis)
• Build scalable pipelines using Apache Beam / Dataflow
• Process large-scale image and sensor datasets
• Ensure reliability through monitoring, observability, and cost‑aware design
• 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
• Work closely ... etc works ... etc.

Requirements

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Nice to Have

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