Senior Machine Learning Engineer

Jobtailor; Kraków; On-site; PLN 180,000 - 260,000; Full time

Job summary

Jobtailor in Kraków, Poland seeks an experienced ML Engineer to own and deliver ML-powered product features end-to-end. You will work with scientists to productionise research outputs and build scalable ML infrastructure.

Ideal candidates have 5+ years in ML/ML Ops, fluent Python, and production experience with LLMs, SQL-based data infra, and cloud deployments (Docker, Kubernetes, AWS). Collaboration with engineers is essential.

Qualifications

• 5+ years of experience in software engineering with focus on ML engineering or MLOps.
• Fluent in Python; working proficiency in Ruby is a plus.
• Solid experience building and operating ML systems in production.
• Experience integrating LLMs into production systems.
• Comfortable with SQL and data infrastructure.
• Experience with containerised deployments (Docker, Kubernetes) and cloud infrastructure (AWS).

Responsibilities

• Own and deliver ML-powered product features end-to-end.
• Work closely with Scientists to productionise research outputs.
• Build and maintain ML infrastructure.
• Contribute to technical design discussions.
• Collaborate with product software engineers.
• Improve reliability, performance, and cost-efficiency of ML systems.
• Mentor more junior engineers.

Skills

ML engineering

Python

Ruby

SQL

Data infrastructure

LLMs in prod

Tools

Docker

Kubernetes

AWS

Job description

Responsibilities

• Own and deliver ML-powered product features end-to-end
• Work closely with Scientists to productionise research outputs
• Build and maintain ML infrastructure
• Contribute to technical design discussions
• Collaborate with product software engineers
• Improve reliability, performance, and cost-efficiency of ML systems
• Mentor more junior engineers

Requirements

• 5+ years of experience in software engineering with a focus on ML engineering or MLOps
• Fluent in Python; working proficiency in Ruby is a plus
• Solid experience building and operating ML systems in production
• Experience integrating LLMs into production systems
• Comfortable with SQL and data infrastructure
• Experience with containerised deployments (Docker, Kubernetes) and cloud infrastructure (AWS)