Hi, I'm Paul! I’m a Machine Learning Engineer at Georgian, a fintech company focused on investing in growth-stage tech companies. I am an experienced machine learning engineer and technical manager. My focus has always been machine learning and data science, but I maintain that knowledge in the full stack gives a good perspective when developing in the ML/DS domain. Skilled as an individual contributor, I also have good technical and people leadership abilities. Recruiting, mentoring/guiding team members and skill development is something that I enjoy. I am an effective collaborator and communicator, and never hesitate to take an active role in connecting stakeholders to discuss and resolve issues. I like to execute and deliver with balanced consideration given to current and future effects on developer productivity and how the change will affect users. Technical Skills • Data Science – Python stack including pandas, scikit-learn, and Tensorflow; expertise in deep learning, NLP, computer vision, supervised and unsupervised classification, regression, and clustering. • ML Service Engineering – integrating data/ML tools into a product, with related cloud services and tooling. • Scalable RESTful/HTTP API services in Node.js and Python. Session cookies, authentication, authorization, rate-limits, caching. Load testing and autoscaling. • Databases – PostgreSQL, Redis, DynamoDB, MongoDB. • Containers – Docker used in dev process, and containers in production (Fargate, Swarm); (~junior with Kubernetes (k8s) but open to opportunity to learn). • Cloud Infrastructure and Deployment – 5+ years of configuring and scaling ML and web services using AWS products. • Continuous testing, model evaluation and retraining, monitoring, deployment. • Git, GitHub, GitLab; JIRA, Asana, Kanban; Agile Scrum. • Linux (ubuntu) preferred, comfortable in macOS. ==== Thanks to Alina Grubnyak (@alinnnaaaa) on Unsplash for the header image https://unsplash.com/photos/ZiQkhI7417A Hi, I'm Paul! I’m a Machine Learning Engineer at Georgian, a fintech company focused on investing in growth-stage tech companies. I am an experienced machine learning engineer and technical manager. My focus has always been machine learning and data science, but I maintain that knowledge in the full stack gives a good perspective when developing in the ML/DS domain. Skilled as an individual contributor, I also have good technical and people leadership abilities. Recruiting, mentoring/guiding team members and skill development is something that I enjoy. I am an effective collaborator and communicator, and never hesitate to take an active role in connecting stakeholders to discuss and resolve issues. I like to execute and deliver with balanced consideration given to current and future effects on developer productivity and how the change will affect users. Technical Skills • Data Science – Python stack including pandas, scikit-learn, and Tensorflow; expertise in deep learning, NLP, computer vision, supervised and unsupervised classification, regression, and clustering. • ML Service Engineering – integrating data/ML tools into a product, with related cloud services and tooling. • Scalable RESTful/HTTP API services in Node.js and Python. Session cookies, authentication, authorization, rate-limits, caching. Load testing and autoscaling. • Databases – PostgreSQL, Redis, DynamoDB, MongoDB. • Containers – Docker used in dev process, and containers in production (Fargate, Swarm); (~junior with Kubernetes (k8s) but open to opportunity to learn). • Cloud Infrastructure and Deployment – 5+ years of configuring and scaling ML and web services using AWS products. • Continuous testing, model evaluation and retraining, monitoring, deployment. • Git, GitHub, GitLab; JIRA, Asana, Kanban; Agile Scrum. • Linux (ubuntu) preferred, comfortable in macOS. ==== Thanks to Alina Grubnyak (@alinnnaaaa) on Unsplash for the header image https://unsplash.com/photos/ZiQkhI7417A

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  Machine Learning Engineer in Georgian

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