Senior Machine Learning Engineer
December 5
Airflow
AWS
Azure
Cloud
Docker
Google Cloud Platform
Hadoop
Java
Kafka
Kubernetes
NoSQL
Python
PyTorch
Scala
Scikit-Learn
Spark
SQL
Tensorflow
Go
Description
• implementing end-to-end solutions for batch and real-time algorithms along with requisite tooling around monitoring, logging, automated testing, model retraining, model deployment and metadata tracking • identifying new opportunities to improve business processes and improve consumer experiences, and prototype solutions to demonstrate value with a crawl, walk, run mindset • working with data scientists and analysts to create and deploy new product features on the ecommerce website, in-store portals and client’s mobile app • establishing scalable, efficient, automated processes for data analyses, model development, validation and implementation • writing efficient and scalable software to ship products in an iterative, continual-release environment • contributing to and promoting good software engineering practices across the team and build cloud native software for ML pipelines • contributing to and re-use community best practices
Requirements
• ability to start immediately • openness to work daily between till 19.00 pm CET • university or advanced degree in engineering, computer science, mathematics, or a related field • 7+ years experience developing and deploying machine learning systems into production • experience working with a variety of relational SQL and NoSQL databases • experience working with big data tools: Hadoop, Spark, Kafka, etc. • experience with at least one cloud provider solution (AWS, GCP, Azure) and understanding of severless code development • experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc. • previous experience developing predictive models in a production environment • MLOps and model integration into larger scale applications • experience with Machine and Deep Learning libraries such as Scikit-learn, XGBoost, MXNet, TensorFlow or PyTorch • exposition to GenAI and solid understanding of multimodal AI via HuggingFace, Llama, VertexAI, AWS Bedrock or GPT • knowledge of data pipeline and workflow management tools • expertise in standard software engineering methodology, e.g. unit testing, test automation, continuous integration, code reviews, design documentation • working experience with native ML orchestration systems such as Kubeflow, Step Functions, MLflow, Airflow, TFX • very good verbal and written communication skills in English • good verbal and written communication skills in English • Work from European Union region and work permit are required • Nice to have: relevant working experience with Docker and Kubernetes
Apply Now