General Responsibilities:
- Develop and implement Machine Learning models, focusing on training process optimization, including parallelization.
- Design and build cloud-based data pipelines, integrating ML models into existing software solutions.
- Create and deploy inference endpoints (APIs) and optimize compute architectures and data structures.
- Implement logging and metric generation for models, ensuring comprehensive monitoring and addressing model degradation.
- Lead the deployment of machine learning models in Azure or AWS cloud environments, managing the full lifecycle from development to production.
- Build CI/CD pipelines for machine learning models using Azure or AWS tools to streamline deployment and updates.
- Collaborate with cross-functional teams to continuously improve and advance technologies and methods for ML systems.
Job Requirements:
- Strong proficiency in Python and relevant scripting languages, with experience in software development and scripting for Machine Learning.
- Expertise with ML libraries and frameworks (e.g., Pandas, Numpy, Scikit-Learn, TensorFlow, PyTorch, Databricks, MLFlow, dvc, dbt) and the ability to select the right tools for the use case.
- Proven experience in optimizing ML training processes, including parallelization techniques to improve model performance.
- Experience building inference endpoints (APIs) and managing compute architecture for efficient model inference and data handling.
- Skilled in implementing monitoring systems, including logging and metric generation for machine learning models.
- Knowledge of cloud platforms (Azure, AWS) for deploying machine learning models and managing model lifecycle, with a focus on addressing model degradation.
- Experience with CI/CD pipelines for ML, using tools such as Azure Pipelines, AWS CodePipeline, or similar.
- Familiarity with data science tools and best practices for ensuring high-quality and efficient ML workflows.
We offer:
- Competitive employee benefits, including comprehensive health insurance, dental and sports coverage, and opportunities for certified training.
- Flexibility in work arrangements, including home office options and flexible working hours.
- A positive, team-oriented environment that fosters mutual trust, creativity, and initiative.
- Opportunities for career growth within a global, innovative framework.
- A diverse, multicultural workplace with a strong emphasis on team collaboration and professional development.
