Machine Learning Infrastructure Engineer
⚲ Warszawa
24 000 - 28 000 PLN brutto (UoP)
Wymagania
- AWS
- Docker
- Kubernetes
- Kafka
- Python
Opis stanowiska
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/MLflowSalary: 24 000 PLN - 28 000 PLN gross on the Contract of Employment
Working model: Hybrid - 3 days/week from the office
Location: ul. Grzybowska 60, Warsaw
Recruitment process:
• A call with MOTIFE Recruiter
• Hiring Manager screening
• Coding interview
• Panel interviews with the team (coding, architecture, and cross-collaboration interviews, Hiring Manager meeting)
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.
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.
What we offer:
• 100% paid medical care
• Multisport
• Creative tax (KUP)
• Home office allowance
• MacBook Pro
Apply now
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.
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/MLflowSalary: 24 000 PLN - 28 000 PLN gross on the Contract of Employment
Working model: Hybrid - 3 days/week from the office
Location: ul. Grzybowska 60, Warsaw
Recruitment process:
• A call with MOTIFE Recruiter
• Hiring Manager screening
• Coding interview
• Panel interviews with the team (coding, architecture, and cross-collaboration interviews, Hiring Manager meeting)
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.
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.
What we offer:
• 100% paid medical care
• Multisport
• Creative tax (KUP)
• Home office allowance
• MacBook Pro
Apply now
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.
🔍 Dekoder Ogłoszenia
🔴
design, build, and maintain low-latency, highly scalable services that make real-time personalization possible
Oczekuje się, że będziesz odpowiedzialny za całościowy cykl życia usług, od projektowania po utrzymanie, co może oznaczać dużą odpowiedzialność i potencjalnie wiele godzin pracy.
🟡
partnering closely with ML Engineers, API Engineers, Platform Engineers, and Product Managers
Będziesz musiał efektywnie komunikować się i współpracować z różnymi zespołami, co wymaga dobrych umiejętności interpersonalnych i zdolności do pracy w zespole.
🟢
bring ML-powered product features into production
Twoja praca będzie miała bezpośredni wpływ na produkty, co jest satysfakcjonujące, ale może też oznaczać presję związaną z terminami i jakością.
🟡
Panel interviews with the team (coding, architecture, and cross-collaboration interviews, Hiring Manager meeting)
Proces rekrutacyjny jest wieloetapowy i może być czasochłonny, wymagając przygotowania na różne rodzaje rozmów.
🟡
Python microservices powering personalized content re
Chociaż ogłoszenie jest w trakcie, sugeruje, że będziesz pracować nad kluczowymi elementami systemu rekomendacji, co może być zarówno wyzwaniem, jak i okazją do rozwoju.