Join our team and be responsible for deploying and scaling machine learning models, especially large language models (LLMs). Collaborate with data scientists to optimize models for cost and performance. Work with software engineers to establish modern machine learning pipelines, ensuring high operational standards using technologies like Python, Java, Sagemaker, Huggingface, and Pytorch.
In the Search & Match domain, you'll contribute to building core infrastructure for recommender systems and search algorithms that connect millions of users meaningfully.
Your responsibilities:
* Deploy and scale ML models, particularly LLMs
* Utilize tools like Huggingface, Pytorch, and cloud services such as AWS; programming in Python and Java
* Collaborate with data scientists, ML engineers, and backend engineers in an agile environment
* Implement DevOps practices including CI/CD, containerization (Docker), Infrastructure as Code (Terraform), and monitoring
* Develop and maintain modern API and microservices architectures
Qualifications:
* Strong Python skills
* Experience with machine learning frameworks like Huggingface and Pytorch
* Experience deploying and scaling ML models with AWS and SageMaker
* Understanding of DevOps principles and modern API/microservices architectures
* Experience with vector databases, semantic search, or event-driven architectures like Kafka is a plus
Additional Information:
We value work-life balance and offer benefits such as:
* 29 vacation days (including recovery days)
* Hybrid working model
* Group insurance (life, pension, disability)
* Hospital insurance
* Flexible compensation plan
* Ongoing development opportunities
* Fitness classes and studio access
* 24/7 employee assistance program
* Free parking and public transport tickets (company cars and fuel card for certain roles)
* Snacks and drinks
* Access to our corporate benefits app
Our commitment to diversity and inclusion is fundamental. We encourage applications from all backgrounds and identities, aiming to recruit, develop, and retain the best talent regardless of personal characteristics.
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