AI/ML Ops Engineer

About Revolte
Revolte is building AI for Software Engineering.
We are creating an AI-native platform that helps engineering teams execute the software delivery lifecycle with speed, quality, and control - from planning and implementation to testing, release, governance, and production feedback.
We're looking for an AI/ML Ops Engineer to build and operate the systems that take AI and ML capabilities from development to reliable production. You'll work closely with AI, backend, and platform engineers to build scalable pipelines, deployment systems, model infrastructure, and observability for AI-powered applications.
Responsibilities
Build and maintain production-grade MLOps and LLMOps pipelines for AI applications.
Automate model training, evaluation, versioning, deployment, monitoring, and rollback workflows.
Build CI/CD pipelines for AI/ML models, services, and supporting infrastructure.
Deploy and operate AI workloads across cloud, containerised, and Kubernetes environments.
Build reliable model-serving and inference infrastructure with a focus on performance, scalability, and cost.
Implement monitoring and observability for model performance, latency, reliability, and infrastructure health.
Work with AI Engineers to optimise models and inference workloads for production.
Manage data, model, and feature pipelines across development, staging, and production.
Troubleshoot production issues across AI applications, models, data pipelines, and infrastructure.
Establish best practices for reproducibility, security, reliability, and governance of AI systems.
Evaluate and adopt emerging AI infrastructure, MLOps, and LLMOps technologies.
What We Are Looking For
1-3 years of experience in MLOps, ML Engineering, AI Infrastructure, DevOps, SRE, or Platform Engineering.
Strong software engineering and automation skills.
Experience taking ML/AI workloads from experimentation to production.
Strong understanding of cloud infrastructure, containers, distributed systems, and deployment workflows.
Strong problem-solving and production troubleshooting skills.
Ability to collaborate effectively with AI, backend, platform, and product teams.
Strong ownership mindset and willingness to work in a fast-moving environment.
Genuine interest in AI, LLMs, AI agents, and production AI systems.
Technical Skills
Strong proficiency in Python, Go, or Bash.
Hands-on experience with AWS, Azure, or Google Cloud.
Experience with Docker and Kubernetes.
Experience with MLflow, Kubeflow, SageMaker, Vertex AI, or similar MLOps platforms.
Experience building CI/CD pipelines using GitHub Actions, GitLab CI, Jenkins, or similar.
Experience with Terraform, Pulumi, or other Infrastructure as Code tools.
Understanding of model training, evaluation, versioning, deployment, and monitoring.
Experience with model serving/inference frameworks such as vLLM, KServe, Triton, or BentoML is a plus.
Familiarity with LLMOps, RAG, embeddings, vector databases, and AI agent workloads.
Experience with Prometheus, Grafana, OpenTelemetry, or similar observability tools.
Strong understanding of Linux, networking, cloud security, IAM, and containerised systems.
Experience with databases, object storage, message queues, and distributed systems is desirable.
Why Join Revolte
Build the infrastructure behind the next generation of AI-powered software engineering.
Work at the intersection of AI, ML, cloud infrastructure, and distributed systems.
Solve challenging problems around model reliability, inference, scalability, observability, and cost.
Work closely with AI, backend, and platform engineers.
Take ownership of systems from architecture and automation through production.
Work with modern AI and cloud technologies and continuously expand your technical expertise.
Join a high-ownership AI-first company where your work directly shapes the engineering foundation.
Grow with Revolte as we build technology that changes how software engineering is done.

Work arrangement
No