4 months ago
Barcelona, SpainStaff+
Responsibilities
- Define the technical vision and roadmap for Preply’s ML platform across teams, products, and business lines.
- Architect platform capabilities spanning experimentation, feature engineering, artifact management, training, deployment, monitoring, retraining, and governance.
- Design cloud-native infrastructure for distributed training and inference, including GPU environments, autoscaling, workload isolation, rollout strategies, and cost optimization.
- Set technical direction for ML CI/CD pipelines with testing, validation, security, performance checks, and release confidence.
- Establish observability standards covering model metrics, service health, alerts, drift detection, data quality, lineage, and business impact.
- Lead GenAI and LLM platform capabilities including gateway services, vector retrieval, prompt experimentation, evaluation, inference optimization, and model serving.
- Build platform abstractions, internal libraries, templates, and self-service tooling for ML Scientists, Data Scientists, and engineers.
- Partner with cross-functional leaders to align platform investments with experimentation velocity, reliability, cost efficiency, and user impact.
- Mentor senior engineers, influence architecture, raise engineering standards, and remove bottlenecks between ML research and production.
Requirements
- 9+ years of engineering experience with significant depth in large-scale ML, data, infrastructure, or platform systems.
- Proven experience architecting and scaling production-grade ML platforms for multiple teams, workflows, and use cases.
- Deep understanding of cloud-native architecture and end-to-end ML workflows, including experimentation, feature management, model versioning, training, deployment, monitoring, benchmarking, and lifecycle management.
- Strong hands-on experience with GCP or AWS, Kubernetes, distributed compute, observability, and infrastructure-as-code practices.
- Experience building enabling tools and platform capabilities for Applied Scientists, Data Scientists, and engineering teams.
- Strong technical judgment across reliability, scalability, security, cost, and developer experience.
- Excellent communication, cross-functional influence, architecture decision-making, and stakeholder alignment skills.
- Demonstrated ability to mentor engineers, raise engineering standards, and multiply team impact.
- Product-impact mindset focused on experimentation velocity, user experience, and measurable business value.
- Familiarity with LLM frameworks and GenAI infrastructure such as LangChain, LlamaIndex, vector stores, retrieval systems, prompt evaluation, model serving, or LLM observability.
Benefits
- Open, collaborative, dynamic, and diverse company culture.
- Monthly allowance for lessons on Preply.com.
- Learning and Development budget and time off for self-development.
- Equity, leave allowance, and health insurance.
- Access to free mental health support platforms.
- Opportunity to support learners and tutors through language learning and teaching across 175 countries.
Tech Stack
Categories
About Preply
Preply builds an online marketplace that connects learners with human tutors for live language lessons, supported by AI tools. Consumers book 1:1 sessions and ongoing courses, while organizations use Preply Business for corporate language training; revenue comes from commissions and subscriptions. Founded in 2012 and privately held, Preply operates globally with 100,000+ tutors teaching 90+ languages.