Senior Machine Learning Engineer

Summary

Join Lokalise, a leading AI-powered translation platform, as a Senior Machine Learning Engineer. You will be responsible for building and owning LLM-powered backend services, designing infrastructure for rapid experimentation with LLMs, and integrating and maintaining LLM observability tooling. Collaborate with Data and ML Scientists to productionize workflows and ensure system reliability and deployability. Contribute to team culture and stay connected to product user needs and industry trends. This role requires 4+ years of experience in building and operating backend systems, strong proficiency in Python, FastAPI, and Pydantic, and a solid understanding of microservice architecture and observability. The position is fully remote but requires residing in specific European countries.

Requirements

• 4+ years of experience building and operating backend systems in production
• Strong proficiency with Python , FastAPI , and Pydantic
• Solid understanding of microservice architecture , scalable distributed systems , and observability , with familiarity using tools like OpenTelemetry , Grafana , or Datadog to monitor both general system health and LLM-specific metrics like latency, token usage, and model performance
• Hands-on experience with prompt engineering in production
• Familiarity with CI/CD , containerisation, and cloud deployment
• Strong sense of ownership

Responsibilities

• Build and own LLM-powered back end services using FastAPI, Pydantic, etc. — ensuring they are scalable, observable, and easy to extend
• Design infrastructure that enables rapid experimentation with LLMs, including A/B testing, feature flagging, and usage analytics
• Integrate and maintain LLM observability tooling (e.g., LiteLLM, Langfuse) to monitor quality, cost, and performance of model calls
• Collaborate with Data and ML Scientists to productionize workflows, share feedback, and continuously improve experimentation speed
• Ensure systems are reliable and deployable with strong CI/CD practices , including instrumentation and alerting
• Contribute to team culture through pairing, mentoring, and sharing learnings to help others grow
• Stay connected to the product by understanding our users' needs, localization workflows, and broader industry trends

Preferred Qualifications

• Experience with LangGraph, multi-modal LLMs and familiarity with tools for LLM integration and observability (e.g. LiteLLM, Langfuse, PromptLayer, or WhyLabs)
• Experience with Lightdash , Snowflake, or modern BI tooling
• Working knowledge of TypeScript , particularly for building or maintaining back end services (e.g., Node.js or serverless APIs)
• Understanding of translation quality metrics (BLEU, chrF, COMET, MQM, METEOR)
• Previous experience with MLOps principles and tooling (e.g. MLflow, Kedro) and/or ML platforms (e.g. SageMaker, Vertex AI)

Benefits

• Competitive salary and employee stock options plan
• Fully remote and flexible working hours
• Co-working budget
• Flexible vacation policy
• Equipment budget to set up your home office
• Learning & Development program
• Health insurance
• Wellness benefits
• Great startup atmosphere, team spirit, and team events