![Allegro](https://media.trabajo.org/img/noimg.jpg)
Software Engineer
4 dni temu
technologies-expected :
Python
technologies-optional :
SQL
about-project :
The MLOps team is a part of the Machine Learning Research lab and provides tools for optimizing, scaling, and deploying advanced machine learning models. We blend artificial intelligence, software engineering, and DevOps expertise to embrace the full potential of research engineers and data scientists from other teams. We orchestrate the entire machine learning lifecycle, from data preprocessing and annotation to model deployment, using the cutting-edge infrastructure of Google Cloud and Kubernetes. We're operating at a massive scale with several terabytes of data processed daily and thousands of predictions per second.
Your daily toolkit will consist of:
Python
Kotlin and Java
Docker and K8s
Google Cloud Platform (Cloud Composer, Dataflow, Vertex AI)
internal Allegro libraries and toolkits
responsibilities :
As a Machine Learning Engineer (Software Engineer - Machine Learning) you will support Research Engineers in building Machine Learning models and then deploy them on production, ensuring high availability and performance. Your work will be related to:
MLOps ecosystem development for ML models training and deployment automation
Gen AI enablement platform development
Model training pipelines development
Production-running models management, monitoring and tweaking
Internal feature-store development
Supporting product teams in ML-based microservices development
Internal data annotation platform development
requirements-expected :
We are looking for people who:
Know ML models lifecycle
Have a practical experience in ML-based solutions development
Are familiar with any cloud platform (preferably Google Cloud Platform)
Have a practical experience in Python microservices and libraries development as well as maintenance
Can independently make decisions within a designated scope and take full responsibility for tasks taken, during their entire lifecycle: from requirements engineering, through implementation to deployment and maintenance
Know English on at least B2 level
offered :
Support from experienced Machine Learning Engineers, Research Engineers, Data Engineers and Data Scientists
A hybrid work model that you will agree on with your leader and the team. We have well-located offices (with fully equipped kitchens and bicycle parking facilities) and excellent working tools (height-adjustable desks, interactive conference rooms)
Annual bonus up to 10% of the annual salary gross (depending on your annual assessment and the company's results)
A wide selection of fringe benefits in a cafeteria plan – you choose what you like (e.g. medical, sports or lunch packages, insurance, purchase vouchers)
English classes that we pay for related to the specific nature of your job
16" or 14" MacBook Pro with M1 processor and, 32GB RAM or a corresponding Dell with Windows (if you don’t like Macs) and other gadgets that you may need
Working in a team you can always count on — we have on board top-class specialists and experts in their areas of expertise
A high degree of autonomy in terms of organizing your team’s work; we encourage you to develop continuously and try out new things
Hackathons, team tourism, training budget and an internal educational platform, MindUp (including training courses on work organization, means of communications, motivation to work and various technologies and subject-matter issues)
benefits :
sharing the costs of sports activities
private medical care
sharing the costs of foreign language classes
sharing the costs of professional training & courses
life insurance
flexible working time
integration events
no dress code
leisure zone
extra social benefits
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