Machine Learning Infrastructure Engineer at Motife Sp. z o.o.

Opis stanowiska:

Najnowsze informacje o pracy w Motife Sp. z o.o. na stanowisko Machine Learning Infrastructure Engineer. If the Machine Learning Infrastructure Engineer wolny etat w Mazowieckie odpowiada Twoim kwalifikacjom, prześlij swoje aktualne CV bezpośrednio przez portal Jobkos.

Pamiętaj, że proces rekrutacji wymaga spełnienia określonych wymogów firmy. Mamy nadzieję, że oferta pracy w Motife Sp. z o.o. na stanowisko Machine Learning Infrastructure Engineer poniżej odpowiada Twoim kwalifikacjom.

Machine Learning Infrastructure EngineerMiejsce pracy: WarszawaTechnologies we useExpected

• AWS
• Google Cloud Platform
• Microsoft Azure
• Postgres
• MySQL
• DynamoDB
• Redis
• Kafka
• RabbitMQ
• SQS

Optional

• Java
• Kotlin
• Go
• C
• C++
• Python

Operating system

• macOS

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 Firma’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

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.

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.

This is how we organize our workThis is how we work

• in house
• you have influence on the technological solutions applied
• you have influence on the product
• agile

Team members

• backend developer
• frontend developer
• fullstack developer
• technical leader
• automated test programmer

This is how we work on a project

• TDD
• Continuous Deployment
• Continuous Integration
• team-level deployment
• test automation

What we offer

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

Benefits

• sharing the costs of sports activities
• private medical care
• remote work opportunities
• corporate gym

Recruitment stages

• A call with MOTIFE Recruiter
• Hiring Manager screening
• Coding interview
• Panel interviews with the team

Motife Sp. z o.o.

MOTIFE is a trusted partner for tech companies choosing Polska to build and grow their engineering and software development capabilities.

We help software companies, startups, fintechs, technology companies, and industry disruptors with their IT recruitment and, wherever necessary, advisory in setting up a presence in Polska and daily operations.

Our end-to-end support helps us build long-term relationships with new IT players, which means we can offer some of the most interesting career opportunities for skilled software and IT professionals like you.

Szczegóły oferty:

• Firma: Motife Sp. z o.o.
• Stanowisko: Machine Learning Infrastructure Engineer
• Miejsce pracy: Mazowieckie
• Kraj: PL

Jak złożyć aplikację:

Po zapoznaniu się z kryteriami i wymaganiami opisanymi w informacjach o pracy Machine Learning Infrastructure Engineer at the office Mazowieckie powyżej, niezwłocznie przygotuj dokumenty aplikacyjne, takie jak list motywacyjny, CV, kopię dyplomu oraz inne załączniki. Wyślij aplikację, klikając 'Następna strona' poniżej.

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