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Senior Machine Learning Engineer
Il y a 2 mois
We are seeking a highly skilled Senior Machine Learning Engineer to join our Artificial Intelligence Engineering team at AXA Group Operations. As a key member of our team, you will play a crucial role in developing and deploying end-to-end machine learning solutions on the Databricks platform.
Key Responsibilities- Enhance Machine Learning Solutions: Develop and deploy high-quality machine learning models on the Databricks platform, from data pre-processing and feature engineering to model training, evaluation, deployment, and monitoring.
- Implement Databricks Templates: Enhance and implement Databricks templates/recipes to boost the scalability of AI use cases.
- Refactor Notebooks: Refactor notebooks into high-quality code scripts that will be part of the ML pipelines.
- Design and Optimize ML Pipelines: Design and optimize ML pipelines on Databricks, leveraging its features and capabilities to streamline the model development and deployment process.
- Build MLOps Infrastructure: Build and maintain scalable and reliable MLOps infrastructure on Databricks, facilitating model versioning, monitoring, and automated deployment.
- Codify Best Practices: Codify best practices for model performance monitoring, model drift detection, and model retraining, ensuring high-quality and up-to-date ML models in production.
- Implement CI/CD Pipelines: Implement repeatable and reliable CI/CD pipelines.
- Implement Data, Model, and Code Tests: Implement data, model, and code tests.
- Stay Up-to-Date with Industry Advancements: Stay up-to-date with the latest advancements in MLOps, LLMOps, and Databricks technologies, and proactively identify opportunities to enhance our ML capabilities.
- Mentor and Provide Technical Guidance: Mentor and provide technical guidance to the Data Science teams across AXA entities.
- Build Assets and Guidelines: Build assets and guidelines with our internal MLOps community.
- Participate in Data Governance Initiatives: Participate in data governance initiatives to ensure the compliance and integrity of the AI Products.
- 5+ Years of Experience: 5+ years of hands-on experience as a ML Engineer in pushing AI Products in production based on MLOps best practices.
- Strong Proficiency in Python: Strong proficiency in Python.
- Familiarity with Cookiecutter and Makefile: Familiar with cookiecutter and Makefile.
- Agile Methodologies: A good understanding of Agile methodologies and a mindset of continuous improvement.
- Excellent Communication Skills: Ability to articulate the results of your work for operational teams, middle, and top management.
- Excellent Interpersonal Skills: Excellent communication in English and interpersonal skills for working in a multicultural work environment.
- Passion for Problem-Solving: Passion about solving challenging problems leveraging new technologies.
- Practical Knowledge of Infrastructure as Code: Practical knowledge of Infrastructure as Code.
- Practical Knowledge of Data and Model Monitoring: Practical knowledge of data and model monitoring to detect data, concept, and target drifts.
- Insurance and Finance Functional Knowledge: Insurance and Finance functional knowledge.
