Experts dedicated to becoming the leaders in providing Big Data, Cloud, Analytics, ML/AI/BI services.
Big data • Hadoop • NoSQL • Spark • Kafka
51 - 200
June 26
Airflow
Apache
AWS
Azure
Bash
Cloud
Docker
Google Cloud Platform
Kubernetes
Python
PyTorch
Ray
Spark
SQL
Tensorflow
Experts dedicated to becoming the leaders in providing Big Data, Cloud, Analytics, ML/AI/BI services.
Big data • Hadoop • NoSQL • Spark • Kafka
51 - 200
• Collaborating with Platform Engineers to set the infrastructure required to run MLOps processes efficiently • Implementing ML workflows / automating CI/CD pipelines • Automating model deployment and implementing model monitoring • Collaborating with Platform Engineers to implement backup and disaster recovery processes for ML workflows, especially models and experiments • Collaborating with stakeholders to understand the key challenges and inefficiencies of Machine Learning project lifecycles within the company • Keeping abreast of the latest trends and advancements in data engineering and machine learning
• Proficiency in Python, as well as experience with scripting languages like Bash or PowerShell • Knowledge of at least one orchestration and scheduling tool, for example, Airflow, Prefect, Dagster, etc • Understanding of ML algorithms and distributed training, e.g., Spark / PyTorch / TensorFlow / Dask / Ray • General knowledge about cloud computing • Familiarity with services related to machine learning (e.g., AWS SageMaker / Azure ML / GCP Vertex AI) • Experience in frameworks such as Databricks or Apache Beam • Familiarity with tools like MLflow, W&B, and Neptune AI from the operations perspective • Experience with containerization technologies like Docker and basic knowledge of container orchestration platforms like Kubernetes • Understanding of continuous integration and continuous deployment (CI/CD) practices, as well as experience with related tools like GitHub Actions or GitLab CI
• 100% remote work • Flexible working hours • Opportunity to learn and develop with the best Big Data experts • International projects • Possibility of conducting workshops and training • Certifications • Co-financing sport card • Co-financing health care • All equipment needed for work
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