Staff Machine Learning Ops Engineer

Stack

Responsibilities

• ▹Define the technical vision and roadmap for Preply's ML platform, supporting growing ML and GenAI adoption across multiple teams, products, and business lines
• ▹Lead the architecture of platform capabilities across the full ML lifecycle: experimentation, feature engineering, artifact management, training, deployment, monitoring, retraining, and governance
• ▹Design cloud-native infrastructure for distributed training and inference, including GPU-based environments, autoscaling, workload isolation, rollout strategies, and cost optimization
• ▹Set the technical direction for CI/CD for ML, embedding testing, validation, security, performance checks, and release confidence into deployment pipelines
• ▹Establish observability standards for ML systems, including model metrics, service health, alerts, drift detection, data quality, lineage, and business-impact monitoring
• ▹Lead the evolution of Preply's GenAI and LLM platform capabilities, including LLM Gateway services, vector retrieval infrastructure, prompt experimentation, evaluation frameworks, latency-optimized inference, and reliable model-serving patterns
• ▹Partner with Applied Science and Data leads, Product leaders, and Engineering teams to align platform investments with experimentation velocity, cost efficiency, operational reliability, and user impact
• ▹Design platform abstractions, internal libraries, templates, and self-service tooling that help ML Scientists and engineers move faster without compromising reliability or security
• ▹Act as a technical multiplier by mentoring senior engineers, influencing architecture, raising standards, and guiding teams through complex platform decisions
• ▹Identify and eliminate bottlenecks in the path from ML research to production

Requirements

• ▹9+ years of engineering experience, with significant depth in large-scale ML, data, infrastructure, or platform systems
• ▹Proven ability to architect and scale production-grade ML platforms that support many teams, workflows, and ML use cases
• ▹Deep understanding of cloud-native architecture and end-to-end ML workflows, including experimentation, feature management, model versioning, training, deployment, monitoring, performance benchmarking, and lifecycle management
• ▹Strong hands-on experience with cloud platforms such as GCP or AWS, Kubernetes, distributed compute, CI/CD, observability, and infrastructure-as-code practices
• ▹Experience building enabling tools and platform capabilities for Applied Scientists, Data Scientists, and engineering teams
• ▹Strong technical judgment, making pragmatic architecture decisions across reliability, scalability, security, cost, and developer experience
• ▹Excellent communication and influence skills, aligning cross-functional stakeholders and translating platform strategy into execution
• ▹Demonstrated ability to mentor engineers and raise engineering standards
• ▹Product-impact mindset: caring about building platform capabilities that accelerate experimentation and improve user experiences

Nice to have

• ▹Familiarity with LLM frameworks and GenAI infrastructure, such as LangChain, LlamaIndex, vector stores, retrieval systems, prompt evaluation, model serving, or LLM observability

Soft skills

What we offer

• ▹An open, collaborative, dynamic and diverse culture
• ▹A generous monthly allowance for lessons on Preply.com, a Learning & Development budget, and time off for self-development
• ▹A competitive financial package with equity, leave allowance, and health insurance
• ▹Access to free mental health support platforms
• ▹The opportunity to unlock the potential of learners and tutors through language learning and teaching in 175 countries

About the company

Preply builds a human-led, tech-enabled, AI-enhanced learning platform used by millions of learners and tutors worldwide. The company recently reached unicorn status with a $150M Series D. Today, 100,000+ tutors teach 90+ languages to learners in 180 countries, as ML and GenAI become increasingly central to the product, marketplace, and operational systems.