Senior Machine Learning Engineer

Location

While our company operates exclusively on a remote basis, you must reside and have the legal right to work in one of the following countries: the United Kingdom, Latvia, Spain, Germany, Denmark, Poland, Portugal, or Ireland.

About

We’re looking for a Senior Machine Learning Engineer to join our growing AI team. You’ll be the technical owner of the systems that power LLM-based localization features — designing reliable, scalable, and observable services from the ground up. You’ll also partner across disciplines to support ML operations and data infrastructure — enabling experimentation and continuous improvement.

This is a role for someone who thrives in complex systems, has a drive for engineering excellence, and enjoys supporting others to succeed.

You will

• 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

You Must Have

• 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

It will be considered a significant advantage if you bring 

(These are not required but will help you hit the ground running.)

• 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)

Our 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