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Machine Learning Infrastructure Engineer
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Offer summary

(Summary generated by AI based on the full job description)

The project focuses on content personalization systems in fitness and wellness, emphasizing real-time personalization. The core stack includes Python, AWS/GCP/Azure, Kubernetes, Docker, REST, gRPC, Kafka, Postgres, Redis. Responsibilities cover building and maintaining Python microservices supporting recommendations, deploying and monitoring ML services in the cloud, performance optimization, and collaboration with ML and product teams. The offer includes 100% paid medical care, Multisport, creative tax benefits, home office allowance, and MacBook Pro.

you can start ASAP

Machine Learning Infrastructure Engineer

Company: Motife Sp. z o.o.

from: 9 June 2026
to: 9 July 2026
24 000 - 28 000 złgross/ mth.contract of employment (full-time)
Salary details
basic salary
Offer parameters
level:senior
working mode:hybrid
Warszawa, Wola
Warszawa, WolaGrzybowska 60View on map

Requirements

Expected technologies

Python
AWS
Postgres
MySQL
DynamoDB
Redis
Kafka
RabbitMQ
SQS
JVM

Operating system

macOS

Our requirements

  • 3+ years of professional software engineering experience and a degree in Computer Science, Engineering, or a related technical field.
  • Strong software engineering fundamentals, including data structures, algorithms, clean code, testing, and reproducibility.
  • Professional experience building backend services in Python; experience with Java, Kotlin, Go, C, or C++ is welcome.
  • Experience designing and building RESTful APIs, gRPC services, or microservices from the ground up.
  • Strong experience deploying and managing production services on AWS or GCP, or Azure.
  • Experience with relational and non-relational databases such as Postgres, MySQL, DynamoDB, or Redis.
  • Experience with event-driven architectures and message queues such as Kafka, RabbitMQ, or SQS.
  • Strong debugging, profiling, and performance tuning skills, including latency tracking, scalability analysis, and production troubleshooting.

Your responsibilities

  • Design, build, and maintain Python microservices powering personalized content recommendations.
  • Productionize, deploy, monitor, and operate machine learning services in cloud-based production environments.
  • Partner with ML Engineers to integrate models into scalable backend services and real-time recommendation workflows.
  • Ensure high availability, low latency, and strong performance through caching, load balancing, auto-scaling, and capacity planning.
  • Own and improve personalization services, including reliability, testability, observability, scalability, and operational readiness.
  • Conduct performance tuning, profiling, and latency optimization for high-traffic recommendation workloads.
  • Collaborate with platform teams to use infrastructure, tooling, and deployment workflows that support fast product iteration.
  • Work with Product Managers, ML Engineers, API Engineers, and Data Engineers to launch ML-powered personalization features.

About the project

We are hiring on behalf of our client, a global innovator in fitness and wellness technology. Their mission is to empower people to live fit, strong, long, and happy lives by delivering integrated experiences to millions of members anytime, anywhere.
We are looking for a Machine Learning Infrastructure Engineer to join the Personalization team, which owns the systems powering content recommendations across the company’s digital ecosystem. In this role, you will design, build, and maintain low-latency, highly scalable services that make real-time personalization possible. You will work hands-on with backend services, cloud infrastructure, model serving, observability, and performance optimization, partnering closely with ML Engineers, API Engineers, Platform Engineers, and Product Managers to bring ML-powered product features into production.
Key takeaways:
Stack: Python, AWS/GCP/Azure, Kubernetes, Docker, REST, gRPC, Kafka/RabbitMQ/SQS, Postgres, MySQL, DynamoDB, Redis, CI/CD, Terraform, Datadog/Grafana/MLflow

This is how we organize our work

This is how we work

in houseyou develop several projects simultaneouslyyou have influence on the technological solutions appliedyou have influence on the productyou focus on product developmentyou focus on code maintenanceagile

Team members

backend developerfrontend developerfullstack developermobile developerdevOpsautomated test programmer

This is how we work on a project

  • Clean Code
  • Continuous Deployment
  • Continuous Integration
  • DevOps
If this sounds like your next step, we’d love to hear from you! Please apply via our careers page and submit your CV in English.
Company

What we offer

  • 100% paid medical care
  • Multisport
  • Creative tax (KUP)
  • Home office allowance
  • MacBook Pro

Recruitment stages

  • 1.
    A call with MOTIFE Recruiter
  • 2.
    Coding interview (1h)
  • 3.
    Panel interviews with the team (2.5h)
Machine Learning Infrastructure Engineer
24k–28k zł / mth. (CoE)
I apply to:
Motife Sp. z o.o.
Warszawa, Wola
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