Staff Machine Learning Ops Engineer

About the role

Preply is scaling an AI‑powered learning platform used by millions worldwide. As a Staff Machine Learning Ops Engineer you will define and evolve the platform that enables machine learning at company scale, partnering with Applied Science, Data, Product and Engineering leaders.

Key responsibilities

• Define the technical vision and roadmap for the ML platform, supporting multiple teams and business lines.
• Architect platform capabilities across the full ML lifecycle: experimentation, feature engineering, training, deployment, monitoring and governance.
• Design cloud‑native infrastructure for distributed training and inference, including GPU environments, autoscaling and cost optimisation.
• Set standards for CI/CD pipelines, embedding testing, validation, security and performance checks.
• Establish observability, drift detection and business‑impact monitoring for ML systems.

Required profile

• 9+ years of engineering experience with deep expertise in large‑scale ML, data or platform systems.
• Proven ability to architect and scale production‑grade ML platforms serving many teams.
• Strong hands‑on experience with GCP or AWS, Kubernetes, distributed compute and infrastructure‑as‑code.
• Excellent communication and influence skills, with a track record of mentoring engineers.

Required skills

• GCP or AWS cloud platforms
• Kubernetes
• CI/CD and infrastructure‑as‑code practices
• Observability and monitoring tools
• LangChain, LlamaIndex, vector stores and retrieval systems
• Prompt evaluation, model serving and LLM observability

What we offer

• Open, collaborative and diverse culture
• Monthly allowance for lessons on Preply.com and a learning & development budget
• Competitive financial package with equity, leave allowance and health insurance
• Free mental‑health support platforms
• Opportunity to impact millions of learners and tutors worldwide