MLOps Engineer

About the role

Zof AI is looking for a MLOps Engineer to own and evolve the platform that runs its AI systems. The role combines AI infrastructure, MLOps, LLMOps and agent platform engineering, focusing on model serving, scaling, GPU efficiency and reliability in a high‑performance environment.

Key responsibilities

• Design and operate model serving, scaling, and compute infrastructure.
• Own GPU and inference efficiency, capacity, and cost management.
• Build provisioning and scaling platforms for AI agents.
• Implement observability, tracing, monitoring and alerting for AI workloads.
• Maintain stable, debuggable and recoverable production AI systems.
• Automate deployment, rollback and environment management processes.
• Define reliability standards and incident response practices for AI workloads.
• Collaborate with engineers to accelerate platform development.

Required profile

• Proven experience operating production AI, ML or high‑scale backend systems.
• Strong foundation in infrastructure and systems engineering.
• Hands‑on experience with cloud platforms, containers and orchestration tools.
• Familiarity with observability and reliability tooling.
• Good judgment on cost, performance and operational trade‑offs.
• Clear written and verbal communication skills.
• Ability to thrive in a fast‑moving environment with high ownership.

Required skills

• Cloud platforms (AWS, GCP, Azure or equivalents)
• Containers (Docker)
• Orchestration (Kubernetes)
• Infrastructure as code (Terraform)
• Observability tooling (monitoring, tracing, alerting)
• GPU clusters and inference servers
• Model gateways

What we offer

• Competitive salary GHS 8,000‑16,000 per month plus equity.
• Full living package including housing, meals, equipment and wellness support.
• Premium AI development tools such as MacBook Pro, Cursor Ultra, Claude, OpenAI Codex.
• Recreational facilities like basketball court, table tennis, foosball and wellness services.