Anton Wolkov, Developer in San Gwann, Malta
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Anton Wolkov

Verified Expert  in Engineering

Big Data Architect and ML Developer Developer

Location
San Gwann, Malta
Toptal Member Since
December 14, 2022

Anton specializes in big data infrastructure architecture and machine learning operations (MLOps). He worked with many high-profile Fortune 500s and startups. He holds a bachelor's degree in computer science, with experience in big data infrastructure development and DevOps. He can get you started with data lakes, onboard data scientists, automation, and create production-grade self-service batch pipelines. Anton prefers using Airflow, Presto, TensorFlow, Kubernetes, and Grafana.

Portfolio

Neobrain
Azure, Python, OVH, Architecture, Artificial Intelligence (AI)...
Proofpoint
Machine Learning Operations (MLOps), DevOps, Amazon Athena, Apache Airflow...
Oracle
Python, Scala, Go, Luigi, Presto DB, Apache Pig, Spark SQL, Pandas, Jenkins...

Experience

Availability

Part-time

Preferred Environment

Ubuntu, Amazon Web Services (AWS), Google Cloud Platform (GCP), MacOS, Databricks, Jupyter Notebook, Zeppelin, IntelliJ IDEA, GitHub

The most amazing...

...thing I've created is a data pipeline infrastructure for six teams worldwide, generating a graph of all internet browsers and mobile phones.

Work Experience

DevOps Expert

2023 - 2023
Neobrain
  • Engaged as a DevOps expert for an AI SaaS in development.
  • Created Terraform and Helm infrastructures for a new production Kubernetes cluster in Azure.
  • Provisioned and configured TPU machines for a one-off training session.
  • Installed and configured a Prefect data pipeline with a CI/CD in GitLab and monitored in Prometheus with Grafana.
Technologies: Azure, Python, OVH, Architecture, Artificial Intelligence (AI), Artificial Intelligence as a Service (AIaaS), Cost Reduction & Optimization, Prefect, TPU, GPU Computing, Google Cloud Platform (GCP), Data Build Tool (dbt), Grafana, Prometheus, Kubernetes, Google Kubernetes Engine (GKE), Azure Kubernetes Service (AKS), Terraform, Helm, Azure Machine Learning, Machine Learning Operations (MLOps), DevOps, CI/CD Pipelines, Machine Learning, Software Architecture, OpenAI GPT-4 API, Large Language Models (LLMs)

Lead MLOps,| DevOps | Software Engineer

2020 - 2023
Proofpoint
  • Integrated multiple teams' data into a natural language processing (NLP) oriented batch data pipeline.
  • Used ETL for data exploration and integration tests on anonymized data.
  • Designed microservices architecture using Python, Docker, Helm, and AWS Service Operator.
  • Built a Jenkins-based CI/CD pipeline Kubernetes deployment for the front and back ends.
  • Merged Prometheus and Grafana dashboards from multiple Amazon EKS clusters using Thanos.
  • Automated PagerDuty incident management with playbooks and CI/CD pipeline deployments.
Technologies: Machine Learning Operations (MLOps), DevOps, Amazon Athena, Apache Airflow, AWS Glue, Kubernetes, MLflow, Prometheus, TensorFlow, Jenkins, Elasticsearch, Amazon Web Services (AWS), Cloud Infrastructure, Cloud Security, Auto-scaling Cloud Infrastructure, AWS Auto Scaling, Linux, Terraform, Back-end, Ubuntu, System Architecture, Scalability, Data Analytics, Google Cloud Platform (GCP), CircleCI, Jupyter Notebook, Zeppelin, Docker, Jenkins Pipeline, Python, Go, Spark SQL, Grafana, MongoDB, Amazon DynamoDB, Redis, Jira, Confluence, Kibana, Spark ML, Vault, Presto DB, Pandas, Apache Kafka, Data Lakes, Apache Superset, Data Pipelines, Ansible, Amazon EKS, Amazon CloudFront CDN, Amazon EC2, Amazon RDS, Amazon OpenSearch, Amazon S3 (AWS S3), PostgreSQL, Apache Hive, IntelliJ IDEA, AWS Lambda, AWS CloudFormation, CI/CD Pipelines, Amazon CloudWatch, Helm, Google Kubernetes Engine (GKE), Big Data Architecture, Continuous Integration (CI), NoSQL, Relational Databases, ELK (Elastic Stack), Data Protection, Cost Reduction & Optimization, Artifactory, Bash, Microservices, Amazon Elastic Container Service (Amazon ECS), AWS DevOps, DNS, API Gateways, Docker Hub, AWS CLI, Amazon Virtual Private Cloud (VPC), Amazon Elastic Container Registry (ECR), Serverless, Identity & Access Management (IAM), Automated Testing, REST APIs, Data Science, Snowflake, Data Engineering, Artificial Intelligence (AI), Machine Learning, Big Data, Shell Scripting, SQL, Architecture, Cloud Architecture, Google Cloud, Git, DevSecOps, Kubernetes Operations (kOps), JavaScript, Data Visualization, Statistical Analysis, Cloud, Data Modeling, Algorithms, Mathematics, Data, Mathematical Analysis, Data Analysis, Data Reporting, API Integration, Postman, Data Integration, Performance Optimization, Cost Management, Database Security, Company Databases, DevOps Engineer, Personally Identifiable Information (PII), Infrastructure as Code (IaC), Site Reliability Engineering (SRE), Infrastructure, Amazon Aurora, Argo CD, Sentry, SonarQube, APIs, Proxies, Developer Portals, Microservices Architecture, GPU Computing, NVIDIA TensorRT, Continuous Delivery (CD), Containers, Argo Workflow, GraphQL, React, TypeScript, IT Support, Software Architecture

Principal Software Engineer

2018 - 2020
Oracle
  • Created a self-service process for data scientists to productize their data proof of concepts (POCs).
  • Integrated metrics collection and reporting into all parts of the pipeline and GitHub pull requests.
  • Migrated AWS EMR workloads using Spark and Kubernetes running on OCI infrastructure.
  • Developed lightweight microservices to handle real-time pixel requests with strict service level agreements (SLAs).
  • Extended the Python and Amazon S3 (AWS S3) library to support Oracle Cloud. Optimized for high-latency operations.
Technologies: Python, Scala, Go, Luigi, Presto DB, Apache Pig, Spark SQL, Pandas, Jenkins, Apache Airflow, MLflow, Kibana, Amazon S3 (AWS S3), Qubole, Kubernetes, Apache Hive, Aerospike, Grafana, Prometheus, Apache Kafka, Machine Learning Operations (MLOps), Elasticsearch, Amazon Web Services (AWS), Cloud Infrastructure, Cloud Security, Auto-scaling Cloud Infrastructure, AWS Auto Scaling, Linux, Terraform, Back-end, Ubuntu, System Architecture, Oracle Cloud, Scalability, Data Analytics, Data Lakes, ETL Tools, ETL Testing, ETL, Tableau, Superset, Apache Superset, Zeppelin, IntelliJ IDEA, Content Delivery Networks (CDN), AWS Glue, AWS ELB, AWS IAM, Oracle Cloud Infrastructure (OCI), TensorFlow, Amazon Athena, Jira, Confluence, DevOps, Amazon Elastic MapReduce (EMR), Ansible, Amazon EKS, AWS Cloud Architecture, Amazon EC2, Amazon RDS, Amazon CloudFront CDN, Amazon OpenSearch, Jupyter Notebook, Docker, ScyllaDB, Redis, Java, Apache Cassandra, Spark ML, PostgreSQL, AWS Lambda, AWS CloudFormation, CI/CD Pipelines, Amazon CloudWatch, Helm, Big Data Architecture, Continuous Integration (CI), Jenkins Pipeline, NoSQL, Relational Databases, ELK (Elastic Stack), Data Protection, Cost Reduction & Optimization, Artifactory, Bash, Microservices, AWS DevOps, DNS, API Gateways, AWS CLI, Amazon Virtual Private Cloud (VPC), Serverless, Automated Testing, REST APIs, Data Science, Prefect, Snowflake, Data Engineering, Artificial Intelligence (AI), Machine Learning, Big Data, Shell Scripting, MySQL, SQL, Architecture, Cloud Architecture, Migration, Cloud Migration, Git, DevSecOps, Kubernetes Operations (kOps), Data Visualization, Statistical Analysis, Cloud, Data Modeling, Algorithms, Mathematics, Data, Mathematical Analysis, Data Analysis, Data Reporting, API Integration, Postman, Data Integration, Apache Spark, Ads, Performance Optimization, Cost Management, Database Security, Company Databases, DevOps Engineer, Personally Identifiable Information (PII), Infrastructure as Code (IaC), Site Reliability Engineering (SRE), Infrastructure, Redshift, SonarQube, Gradle, Harbor, APIs, Proxies, Developer Portals, Microservices Architecture, Spark, Continuous Delivery (CD), Containers, PySpark, Dagster, Software Architecture, Data Migration, Hadoop, EMR, Bitbucket, C, FastAPI

Software Engineer II

2017 - 2018
Amazon.com
  • Onboarded a new real-time database to sync annotators' inputs. Used JavaScript, ETL, report generator, and data exploration tools for AI experiments and proof of concepts (POCs).
  • Repurposed an internal voice annotation platform to be used for computer vision.
  • Automated status reporting from an experiment management platform to Confluence.
  • Created a Jira ticket templating system to simplify operational process status tracking.
Technologies: Spark SQL, Spark ML, PostgreSQL, Amazon S3 (AWS S3), Jupyter Notebook, Zeppelin, RethinkDB, Java, Python, Amazon Elastic MapReduce (EMR), Vault, PyTorch, Machine Learning Operations (MLOps), Elasticsearch, Amazon Web Services (AWS), Cloud Infrastructure, Cloud Security, Auto-scaling Cloud Infrastructure, AWS Auto Scaling, Linux, Back-end, System Architecture, Scalability, Data Analytics, Data Lakes, ETL, ETL Tools, Data Pipelines, Apache Superset, Superset, Amazon Athena, Apache Kafka, Amazon DynamoDB, Computer Vision, Computer Vision Algorithms, Generative Pre-trained Transformers (GPT), GPT, Natural Language Processing (NLP), Jenkins Pipeline, Tableau, Ubuntu, AWS IAM, AWS ELB, ETL Testing, Amazon EKS, Amazon RDS, Amazon CloudFront CDN, Amazon EC2, Amazon OpenSearch, Docker, Jenkins, Redis, Jira, Confluence, Kibana, Pandas, DevOps, IntelliJ IDEA, AWS Lambda, CI/CD Pipelines, Big Data Architecture, Continuous Integration (CI), NoSQL, Relational Databases, ELK (Elastic Stack), Data Protection, Cost Reduction & Optimization, Bash, Microservices, AWS DevOps, AWS CLI, Serverless, REST APIs, Data Science, Data Engineering, Artificial Intelligence (AI), Machine Learning, Big Data, Shell Scripting, SQL, Architecture, Cloud Architecture, Migration, Cloud Migration, Git, HTML, JavaScript, Data Visualization, Statistical Analysis, R, Cloud, Data Modeling, Algorithms, Mathematics, Data, Mathematical Analysis, Data Analysis, Generative Adversarial Networks (GANs), Image Processing, Generative Design, 3D Modeling, Data Reporting, API Integration, Postman, Data Integration, Apache Spark, Performance Optimization, Database Security, Amazon SageMaker, Company Databases, DevOps Engineer, Personally Identifiable Information (PII), Site Reliability Engineering (SRE), Infrastructure, Redshift, Gradle, APIs, Proxies, Developer Portals, Microservices Architecture, Spark, Continuous Delivery (CD), Containers, PySpark, Software Architecture, Data Migration, Hadoop, EMR, JW Player

Software Engineer II

2014 - 2017
Microsoft
  • Integrated users and file APIs from Microsoft Office 365, Google, ServiceNow, Salesforce, and Okta. Used custom asynchronous distributed rate limiter logic.
  • Created a data playground and scale test with automated CI/CD pipelines for data science proof of concepts (POCs). Utilized a huge anonymized production data sample.
  • Integrated data pipelines to Splunk monitoring. Continued with later iterations of Apache Flink, which were integrated into Prometheus and Grafana.
  • Optimized MongoDB and Elasticsearch-based pipelines to scale for all of Microsoft's customers' data from Outlook and SharePoint.
Technologies: Java, Python, Apache Flink, Splunk, Kibana, Jenkins, Azure, Elasticsearch, MongoDB, Apache Ignite, Apache Cassandra, Amazon S3 (AWS S3), Azure IaaS, Amazon Web Services (AWS), Cloud Infrastructure, Cloud Security, Auto-scaling Cloud Infrastructure, AWS Auto Scaling, Linux, Terraform, Back-end, Ubuntu, System Architecture, Scalability, Data Analytics, Scala, ETL, Data Lakes, Data Pipelines, Flink, ETL Tools, ETL Testing, AWS ELB, Apache Kafka, Anomaly Detection, Jenkins Pipeline, Azure Blobs, IntelliJ IDEA, Chef, RabbitMQ, Amazon EC2, Amazon CloudFront CDN, Amazon OpenSearch, Jupyter Notebook, Docker, Machine Learning Operations (MLOps), Redis, Jira, Confluence, DevOps, AWS Lambda, CI/CD Pipelines, Big Data Architecture, Continuous Integration (CI), NoSQL, ELK (Elastic Stack), Data Protection, Cost Reduction & Optimization, Bash, Microservices, AWS DevOps, AWS CLI, Serverless, Identity & Access Management (IAM), Node.js, Automated Testing, REST APIs, Data Science, Data Engineering, Artificial Intelligence (AI), Machine Learning, Big Data, Shell Scripting, Nagios, HAProxy, SQL, Architecture, Cloud Architecture, Migration, Cloud Migration, Git, DevSecOps, Data Visualization, Statistical Analysis, Cloud, Data Modeling, Algorithms, Mathematics, Data, Mathematical Analysis, Data Analysis, Data Reporting, API Integration, Postman, Data Integration, Swagger, Performance Optimization, Database Security, Company Databases, Personally Identifiable Information (PII), Infrastructure as Code (IaC), Infrastructure, Amazon Aurora, Azure Kubernetes Service (AKS), Gradle, APIs, Proxies, Developer Portals, Microservices Architecture, Continuous Delivery (CD), Microsoft Power BI, Containers, Django, Azure Machine Learning, Software Architecture, Data Migration

Android Automation App

My university project was to create a robust, free, and intuitive automation app for Android similar to Tasker. I included natural language descriptions and sharing capabilities. The app was downloaded over 100,000 times and was translated into eight languages by volunteers.

Hackathon Project

A hackathon project. It scans your email (Gmail, Outlook) for receipts with links and downloads the files from said links. I set it up to upload and attach them to the original message. The project was written in Python and hosted on Google Cloud using Cloudflare and content delivery networks (CDN).

Languages

Python, Go, Java, Bash, Snowflake, SQL, HTML, JavaScript, GraphQL, TypeScript, C, Scala, R

Frameworks

Presto DB, Apache Spark, Swagger, Spark, Django, Hadoop

Libraries/APIs

Luigi, Spark ML, Pandas, TensorFlow, Jenkins Pipeline, REST APIs, React, PySpark, PyTorch, Node.js

Tools

Jenkins, Apache Airflow, Spark SQL, Grafana, Amazon OpenSearch, Jira, Kibana, Amazon Elastic MapReduce (EMR), Vault, Qubole, Amazon Athena, Terraform, Tableau, Superset, IntelliJ IDEA, CircleCI, AWS ELB, AWS IAM, Chef, RabbitMQ, Ansible, Amazon EKS, Amazon CloudFront CDN, AWS CloudFormation, Amazon CloudWatch, Helm, ELK (Elastic Stack), GitHub, Artifactory, Confluence, Amazon Elastic Container Service (Amazon ECS), Docker Hub, AWS CLI, Amazon Virtual Private Cloud (VPC), Amazon Elastic Container Registry (ECR), Nagios, Git, Postman, Amazon SageMaker, Azure Kubernetes Service (AKS), Sentry, SonarQube, Gradle, Microsoft Power BI, Azure Machine Learning, Bitbucket, Splunk, Apache Ignite, AWS Glue, Flink, BigQuery, Google Kubernetes Engine (GKE), JW Player

Paradigms

DevOps, ETL, Anomaly Detection, Continuous Integration (CI), Microservices, Automated Testing, Data Science, DevSecOps, Microservices Architecture, Continuous Delivery (CD)

Platforms

Google Cloud Platform (GCP), Jupyter Notebook, Zeppelin, Docker, Kubernetes, Azure, Apache Kafka, Amazon Web Services (AWS), Linux, Ubuntu, Azure IaaS, Oracle Cloud Infrastructure (OCI), Amazon EC2, AWS Lambda, Harbor, Apache Flink, Android, Apache Pig

Storage

Elasticsearch, MongoDB, Redis, Amazon S3 (AWS S3), PostgreSQL, RethinkDB, Apache Hive, Auto-scaling Cloud Infrastructure, Oracle Cloud, Data Lakes, Data Pipelines, Amazon DynamoDB, Azure Blobs, NoSQL, Relational Databases, MySQL, Google Cloud, Data Integration, Database Security, Company Databases, Redshift, Amazon Aurora, Aerospike, ScyllaDB, OVH

Other

Machine Learning Operations (MLOps), Prometheus, MLflow, Cloudflare, Cloud Infrastructure, Cloud Security, AWS Auto Scaling, Back-end, System Architecture, Scalability, Data Analytics, ETL Tools, ETL Testing, Apache Superset, Content Delivery Networks (CDN), Natural Language Processing (NLP), Amazon RDS, AWS Cloud Architecture, CI/CD Pipelines, Big Data Architecture, Data Protection, Cost Reduction & Optimization, AWS DevOps, DNS, API Gateways, Serverless, Identity & Access Management (IAM), Data Engineering, Artificial Intelligence (AI), Machine Learning, Big Data, Shell Scripting, HAProxy, Architecture, Cloud Architecture, Migration, Cloud Migration, Kubernetes Operations (kOps), Data Visualization, Statistical Analysis, Cloud, Data Modeling, Algorithms, Mathematics, Data, Mathematical Analysis, Data Analysis, Generative Adversarial Networks (GANs), Image Processing, Generative Design, 3D Modeling, Data Reporting, API Integration, Ads, Performance Optimization, Cost Management, DevOps Engineer, Personally Identifiable Information (PII), Infrastructure as Code (IaC), Site Reliability Engineering (SRE), Infrastructure, Argo CD, APIs, Proxies, Developer Portals, GPU Computing, NVIDIA TensorRT, Containers, Argo Workflow, IT Support, Software Architecture, OpenAI GPT-4 API, Data Migration, EMR, Large Language Models (LLMs), FastAPI, GitHub Actions, Apache Cassandra, Computer Vision, Computer Vision Algorithms, Prefect, GPT, Generative Pre-trained Transformers (GPT), Dagster, Google BigQuery, Artificial Intelligence as a Service (AIaaS), TPU, Data Build Tool (dbt)

2009 - 2014

Bachelor's Degree in Computer Science

Technion – Israel Institute of Technology - Haifa, Israel

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