Lead Assistant Manager specializing in Advanced AI & ML at data-driven organization. Oversee deployment and monitoring of machine learning models collaborating with cross-functional teams.
Responsibilities
Develop and maintain end-to-end Data Engineering pipelines for deploying, monitoring, and scaling machine learning models.
Collaborate with data scientists, software engineers, and DevOps teams to ensure seamless integration of ML models into production systems.
Optimize model deployment processes by leveraging containerization technologies such as **Docker or Kubernetes**.
Implement continuous integration/continuous deployment (CI/CD) practices for ML model development lifecycle management.
Monitor deployed ML models in production environments to identify performance issues or anomalies.
Work closely with cross-functional teams to troubleshoot issues related to model performance or data quality in production systems.
Stay up-to-date with the latest advancements in MLOps toolkits, frameworks, best practices, and industry trends.
Requirements
Bachelor's degree in Computer Science or a related field; advanced degree preferred.
Minimum 5 years of experience working as an MLOps Engineer or similar role within a data-driven organization.
Experience with Kubernetes and KubeFlow is mandatory.
Strong understanding of machine learning concepts and algorithms.
Proficiency in Python developing ML pipelines/scripts.
Experience with popular MLOps toolkits such as Kubeflow Pipelines, TensorFlow Extended (TFX), MLflow, etc., is essential
Solid knowledge of containerization technologies like Docker and Kubernetes for deploying ML models at scale.
Familiarity with cloud platforms like AWS/Azure/GCP for building scalable infrastructure solutions is highly desirable
Experience with version control systems like Git/GitHub for managing code repositories
Excellent problem-solving skills with the ability to analyze complex technical issues related to ML model deployments.
Wundmanager responsible for planning and conducting wound visits at nursing home. Collaborating with medical staff and ensuring quality of care in Coesfeld, Germany.
Aufnahme - und Belegungsmanager managing admissions and placements for a leading nursing home operator. Involves coordination with residents, families, and healthcare providers.
Wundmanager for Germany's largest nursing home operator, focuses on wound care and individual resident care. Collaborates with doctors and trains nursing staff.
Managing resident admissions and scheduling for a leading German nursing home operator. Engaging with medical staff and families for optimal resident care and placement.
Wundmanager responsible for wound management and training nursing staff in a top German care home operator. Join a team committed to high - quality patient care and continuous improvement.
Wundmanager at Germany's largest nursing home operator focusing on wound management and resident care. Collaborating with teams to ensure quality care in Bramsche, Germany.
Wundmanager responsible for wound management and nursing care for residents at a leading German nursing home operator. Focused on providing high - quality care with extensive support and benefits.
Media Intelligence Manager in Frankfurt identifying media trends and summarizing them for clients. Engaging with a global customer base in finance sector.
(Senior) System Manager at Maurer Electronics GmbH handling IT systems and complex deployments. Leading projects while optimizing operational processes and collaborating with cross - functional teams.