Alexander Eckert
Senior Software Engineer @Bosch Center For Artificial Intelligence Bcai
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WORK HISTORY
Senior Software Engineer @Bosch Center For Artificial Intelligence Bcai
Software engineering- Technical product owner for a cloud-based AI development platform on Azure that enables labeling, ML model training, and sped-up productization of state of the art computer vision deep learning models from research for classification, segmentation and generative AI use cases (Python, Azure, AzureML, K8s, Postgres)- Development of service for ML Model Monitoring (Spark Streaming, Kafka, K8s, Postgres)- Component owner for ML model serving and deployment solution for automated optical inspection in manufacturing deployed in multiple plants and projects (Python, Docker, K8s, gRPC, Protobuf, TensorFlow, Grafana/Prometheus, Splunk, CI/CD)• Data engineering: Processing large data sets with distributed computing frameworks and tools such as Kafka/Spark/HDFS/TensorFlow
EDUCATION
Karlsruhe Institute of Technology (KIT)
Bachelor of Science (B.Sc.), Information Engineering and Management
Karlsruhe Institute of Technology (KIT)
Master of Science (M.Sc.), Information Engineering and Management
SKILLS
ABOUT ALEXANDER ECKERT
I am a Senior Software Engineer with a decade of experience designing, operating, and shipping distributed systems and MLOps platforms and products across cloud-scale (Azure, AWS, IBM Cloud) and on-premises environments. My background spans development-centric roles, including serving as a Technical Product Owner and Backend Lead. I thrive in globally distributed, cross-functional teams, with a core focus on:• End-to-End AI & GenAI Services: Translating cutting-edge research into scalable, customer-oriented machine learning services. My expertise covers the full model lifecycle from training to inference, with extensive past experience in computer vision and a current focus on advanced time series services.• Cloud-Native Architecture: Designing and operating highly scalable SaaS platforms and robust microservices using Kubernetes, Docker, gRPC, and Python.• Distributed Computing & Data Engineering: Industrializing ML solutions and building reliable data pipelines for data lakes using Apache Spark, Kafka and Databricks.
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