Informacje o stanowisku
For one of our top clients from we are looking for an experienced Machine Learning Engineer.
A successfully hired specialist will be playing a pivotal role in enhancing and modernizing applications while maintaining their resilience and availability. Collaboration with fellow developers is central to this role, utilizing expertise in Python and Machine Learning.
- Degree in Computer Science or related fields
- Experience in Python
- At least 5 years of proven industry experience in microservices
- Experience with Infrastructure as code, cloud solutions, and orchestration tools
- Familiarity with CI/CD, ETL, big data tools, and mainstream ML libraries
- Experience working with real-time monitoring/alerting components
- Experience with distributed cache systems
For one of our top clients from we are looking for an experienced Machine Learning Engineer.
A successfully hired specialist will be playing a pivotal role in enhancing and modernizing applications while maintaining their resilience and availability. Collaboration with fellow developers is central to this role, utilizing expertise in Python and Machine Learning.
,[Design and develop highly scalable machine learning infrastructure to support high throughput and low latency, Serve ML models to downstream applications, ensuring accessibility, scalability, and security, Manage model versions and ensure correct versions are served to clients, with rollback mechanisms for issues, Monitor deployed models for issues like concept drift, data drift, and model degradation, resolving them promptly, Develop, test, deploy, and maintain data and model training pipelines to support ML products, Integrate serving infrastructure with data pipelines, monitoring tools, and alerting systems for seamless communication, Constantly review and optimize the ML serving system for efficiency, reliability, and speed, automating tasks as needed, Research and stay up-to-date with the latest machine learning serving technologies and industry trends, Experiment with new scalable machine learning serving architectures and create quick prototypes or proof-of-concepts, Streamline model deployment, unit testing, integration testing, stress testing, and shadow testing, Work with ML engineers to deploy and serve production-grade, state-of-the-art machine learning models at scale Requirements: Python, AWS, HTTP, REST API, Git, Terraform, Big data, Docker, Kubernetes, PyTorch, TensorFlow, Spark Tools: . Additionally: International projects, Long-term cooperation, Sport subscription, Training budget, Private healthcare, Masterclazz training, Free coffee, Canteen, Bike parking, Gym, Playroom, Free snacks, Shower, Free beverages, Modern office, No dress code.
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