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Preply is a unicorn edtech platform (Series D, $150M) that connects 100,000+ tutors teaching 90+ languages to learners in 180 countries. The company is integrating GenAI into its core product strategy to enhance personalized learning experiences.
The GenAI Platform team sits within Platform Engineering and builds shared infrastructure enabling product teams to develop, evaluate, deploy, and operate GenAI safely at scale. The platform encompasses a GenAI gateway, model and prompt lifecycle management, evaluation frameworks, observability, cost controls, and guardrails. The team works closely with ML Platform (core ML workflows) and Agentic Platform (agent orchestration, state management, tool integration) to provide product teams with a consistent foundation for user-facing AI experiences and autonomous agents.
As a Senior ML Platform Engineer, you will design and build systems behind production GenAI workloads, driving expansion of the GenAI Platform and converting recurring engineering needs into reliable self-service capabilities. This is a hands-on senior role with broad technical influence—you'll write production code, shape platform abstractions and operational standards, and partner with Applied Science, Data, Product, Security, and Engineering teams.
Key responsibilities:
- Architect a unified gateway with automated routing, quota controls, and resilient fallback systems across model vendors
- Drive system efficiency and low latency through dynamic traffic management, response caching, token budgeting, and cost allocation controls
- Establish robust evaluation mechanisms to guarantee high precision, stability, and safety in model outputs
- Deliver system observability with deep tracing, performance telemetry, cost analytics, continuous monitoring, and alerting across GenAI lifecycles
- Standardize prompt engineering workflows with automated versioning, testing, governance, and CI/CD integrations
- Embed platform guardrails alongside Security and Privacy experts to enforce policies and safe production defaults
- Maintain sustainable incident response, blameless postmortems, and comprehensive monitoring for GenAI stacks
The role emphasizes hands-on technical work, architectural influence, and cross-functional collaboration in a small team with significant ownership.
REQUIREMENTS:
- 5+ years of proven track record designing, building, and operating backend services or ML infrastructure handling production traffic
- Strong Python skills and experience building developer-facing APIs/SDKs or shared libraries
- Practical experience with GenAI systems, including vector retrieval, external provider APIs, and common issues
- AI Expertise: hands-on experience as a forefront user of Agentic AI; ability to influence beyond code generation on architecture, business logic, and security; experience using AI as a thought partner and setting up quality gates and safety nets; capability to propose AI-native alternatives
- Sound knowledge of distributed systems (high availability, concurrency, caching, rate limiting)
- Experience with at least one major public cloud and its services/infrastructure (preferably AWS)
- Hands-on experience with distributed tracing, system telemetry, SLOs, and incident triage
- Strong communication skills and C1 English level
- Willingness to join a paid on-call rotation
NICE TO HAVE:
- Experience operating AI gateways or scalable model serving infrastructure
- Familiarity with evaluation suites, prompt management, vector databases, or customized GenAI observability tooling
- Experience with Metaflow, Databricks, or AWS SageMaker
- Knowledge of hosting open-source foundation models, optimizing GPU compute, dynamic scaling, and infrastructure cost controls
- Familiarity with agentic workflows, multi-agent frameworks, and tool-use patterns
