Senior ML Platform Engineer (GenAI Platform)

Preply; United States; Remote; USD 140,000 - 190,000; Full time

Job summary

Preply is seeking a Senior ML Platform Engineer to design and build the systems behind production GenAI workloads. You will drive the evolution of our GenAI Platform and turn recurring engineering needs into reliable self-service capabilities.

This hands-on role offers broad technical influence and the chance to shape system architecture, platform direction, and cross‑functional collaboration with Applied Science, Data, Product, Security and Engineering teams.

Responsibilities

• 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

Skills

Production code

Platform architecture

CI/CD

Observability

GenAI

Job description

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.

Meet the team!

The GenAI Platform team sits within Platform Engineering. We build the shared infrastructure that helps product teams develop, evaluate, deploy and operate GenAI safely at scale. Our scope includes the GenAI gateway, model and prompt lifecycle, evaluation, observability, cost controls and guardrails.We work closely with ML Platform, which supports core machine learning workflows, and Agentic Platform, which provides agent orchestration, state management and tool integration. Together, we give product teams a consistent foundation for user-facing AI experiences and autonomous agents.We work in small teams with significant ownership, empowering you to directly shape system architecture, technical direction, and platform evolution. Learn more through our Engineering Blog, Tech Radar, and YouTube channel.

What you’ll be doing:

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.

In this role, your responsibilities include:

• 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