About

Paul M. is a Senior Full Stack Engineer at Discogs with over 13 years of experience in distributed large-scale networks, data engineering, cloud architecture development, edge computing, and data mining. He is a Senior software developer and data engineer of distributed systems and data science applications utilizing emerging technologies and advanced machine learning. He is a Deep Learning/AI expert with extensive experience working with the world’s largest and most complex data sets available. Paul is proficient in various computer languages including Scala, C/C++, R, Python, Java, RESTful APIs, bash/tcsh, (X)HTML(5), XML, XSLT, MEAN stack, NodeJS, (c)make. He has hands-on experience with software packages such as Pandas, NumPy, SciPy, Scikit-Learn, hg/Git, OpenCV, TensorFlow, Keras, Enzo, yt, pytorch/fast.ai. He has worked with applications like Maple, Mathematica, Matlab/Octave, Drupal, Moodle, Django, Flask, Pyramid, TeX, LaTeX, Gnuplot, GIMP/Photoshop, Inkscape/Illustrator, Cloud Computing. Paul has a strong background in DevOps and has worked with OpenStack, AWS, MS Azure, Google Cloud, Firewall, RAID, Backup tools, DNS, SSH/SSL, Apache, NGINX, Tomcat, Jenkins, Jira, HDFS, MySQL, PostgreSQL, Graph DBs (Neo4J, OrientDB), MongoDB, Redis, Docker, Kubernetes, ETL, NFS, LDAP, Git, GitHub, GitLab, FTP, Post-fix, IMAP/POP, spam filters. He is also experienced in Big Data technologies such as Hadoop (HDFS/YARN/HIVE/HBase/Spark), Kafka, Dask. Paul has worked with sfl scientific as a Senior Data Engineer and with Memorial Sloan Kettering Cancer Center as a Bioinformatics Software Engineer III. He holds a Bachelor of Science degree in Computer Science and Mathematics from Loyola University Chicago School of Education. Overall, Paul has 12.19 years of relevant experience in Data Engineering, HDFS, AI, Software Engineer, AWS, Keras, Neo4j, OpenCV, Deep Learning, Spark, Scikit, Big Data, Redis, Kubernetes, Docker, ML, Data Scientist, TensorFlow, Pandas, MySQL, MongoDB, Hadoop, Kafka, Jenkins, DevOps, E