Senior ML Platform Engineer (GenAI Platform)

• Proven track record (5+ years) 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: You're a forefront user of Agentic AI. You're able to bring hands-on experience and start influencing the team beyond code generation; reserving judgment for architecture, business logic, and security, using AI as a thought partner and being able to set up quality gates and safety nets to enhance existing engineering workflows and propose AI-native alternatives.

• Sound knowledge of distributed systems, including high availability, concurrency, caching and rate limiting.

• Experience with at least one major public cloud, its services and infrastructure (preferably AWS).

• Hands-on experience with distributed tracing, system telemetry, SLOs, and incident triage.

• Strong communication skills and at least C1 English level, plus willingness to join a paid on-call rotation.

• 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.

• An open, collaborative, dynamic, and diverse culture;

• A generous monthly allowance for lessons on Preply.com, Learning & Development budget, and time off for your self-development;

• A competitive financial package with equity, leave allowance and health insurance;

• Not in Barcelona? We offer an attractive relocation package to join us in our Preply Barcelona Hub

• Access to free mental health support platforms;

• Access to Gympass-partnered wellness and gym centers throughout Spain to promote and support well-being and physical health;

• The opportunity to unlock the potential of learners and tutors through language learning and teaching in 175 countries (and counting!).

We power people's progress.

At Preply, we're all about creating life-changing learning experiences. We help people discover the magic of the perfect tutor, craft a personalised learning journey, and stay motivated to keep growing. Our approach is human-led, tech-enabled - and it's creating real impact.

We've just reached unicorn status with a $150M Series D, accelerating our vision to transform education through human-led, AI-enhanced learning. Today, 100,000+ tutors teach 90+ languages to learners in 180 countries - and we're only getting started. As a category-defining company, we're shaping what the future of learning looks like at global scale.

Every Preply lesson sparks change, fuels ambition, and drives progress that matters. Joining Preply means helping define the future of education at global scale, and building something that truly matters for millions of people, every day.

GenAI is central to Preply's product strategy. As a Senior ML Platform Engineer, you'll design and build the systems behind production GenAI workloads. You will drive the expansion of our GenAI Platform, and turn 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.

• Architect unified gateway with automated routing, quota controls, and resilient fallback systems across model vendors.

• Drive system efficiency and low latency via 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, providing deep tracing, performance telemetry, cost analytics, continuous monitoring, and alerting across GenAI lifecycles.

• Standardize prompt engineering workflows with automated versioning, automated testing, governance, and CI/CD integrations for production delivery.

• Embed platform guardrails alongside Security and Privacy experts to enforce policies, and safe production defaults automatically.

• Maintain sustainable incident response, blameless postmortems, and comprehensive monitoring for GenAI stacks.