16.06.2025 aktualisiert
100 % verfügbar
Machine Learning Engineer with Deep Learning and Data Engineering Expertise
Heppenheim, Deutschland
Weltweit
BS in Computer ScienceSkills
AirflowKünstliche Neurale NetzwerkeComputer VisionBig DataBigqueryC++DatenbankenContinuous IntegrationInformation EngineeringETLDatensystemeApache HadoopApache HiveBildverarbeitungPythonPostgresqlMachine LearningMongodbMysqlObjekterkennungTensorflowSQLWorkflowsPytorchApache SparkDeep LearningKerasKubernetesCassandraApache KafkaMachine Learning OperationsDockerProgramming Languages
Deep Learning
Expertise in deep learning frameworks including TensorFlow, PyTorch, and Keras. Experience with neural network architectures like BiSeNet, PIDNet, Yolo, and FasterRCNN for computer vision tasks.
Data Engineering
Proficiency in building ETL pipelines using Spark, Hadoop, and SQL. Experience with cloud platforms like GCP and tools such as BigQuery, Composer, and Dataproc for end-to-end data solutions.
MLOps
Knowledge of ML deployment workflows using DVC, MLFlow, and Apache Airflow. Experience with containerization using Docker and Kubernetes for model deployment and CI/CD pipelines.
Programming Languages
Proficiency in Python and C++ for machine learning model development and optimization.
Big Data Technologies
Experience with Spark, Hadoop, Hive, and Kafka for processing and analyzing large datasets.
Database Systems
Knowledge of various database systems including PostgreSQL, MySQL, MongoDB, and Cassandra.
Computer Vision
Expertise in object detection, segmentation, and image processing using various neural network architectures and techniques.
Expertise in deep learning frameworks including TensorFlow, PyTorch, and Keras. Experience with neural network architectures like BiSeNet, PIDNet, Yolo, and FasterRCNN for computer vision tasks.
Data Engineering
Proficiency in building ETL pipelines using Spark, Hadoop, and SQL. Experience with cloud platforms like GCP and tools such as BigQuery, Composer, and Dataproc for end-to-end data solutions.
MLOps
Knowledge of ML deployment workflows using DVC, MLFlow, and Apache Airflow. Experience with containerization using Docker and Kubernetes for model deployment and CI/CD pipelines.
Programming Languages
Proficiency in Python and C++ for machine learning model development and optimization.
Big Data Technologies
Experience with Spark, Hadoop, Hive, and Kafka for processing and analyzing large datasets.
Database Systems
Knowledge of various database systems including PostgreSQL, MySQL, MongoDB, and Cassandra.
Computer Vision
Expertise in object detection, segmentation, and image processing using various neural network architectures and techniques.
Sprachen
Englischverhandlungssicher
Projekthistorie
Built an ETL pipeline for anti-money laundering machine learning model using Spark/Hadoop and SQL. Utilized GCP stack for ETL pipeline creation and implemented CI/CD jobs for automatic deployment.
Worked on details detection using sahi library and Yolo object detection model. Tested nebullvm acceleration library for bugs.
Trained instance segmentators on BiSeNet and PIDNet backbones for real-time segmentation, improving performance from 55% mIoU to 70% mIoU. Developed data pipelines and containerized applications for deployment.