Site Reliability Machine Learning

MICHAEL GRINGAUZ

Toronto, Ontario - *******.********@*****.*** - 647-***-****

linkedin.com/in/michael-gringauz - github.com/mgauz01 Results-driven professional with expertise in Backend Engineering, DevOps, and Site Reliability Engineering (SRE), specializing in scalable, high-performance systems. Strong command of cloud technologies, Infrastructure as Code

(IaC), automation, and observability, with a proven ability to bridge development and operations seamlessly. Passionate about architecting resilient systems, optimizing reliability, and solving complex technical challenges through innovative programming and cloud-native solutions. Adept at incident response, performance tuning, and CI/CD pipelines, ensuring operational excellence across the stack. Seeking roles that leverage my full-stack infrastructure expertise to build robust, scalable backend systems while driving DevOps/SRE best practices.

TECHNICAL SKILLS

Data Solutions: PostgreSQL, MySQL, Data Lakes, MongoDB, GraphQL, PySpark, Hadoop, Spark Hive, AWS EMR, RDS, Aurora, ElastiCache

Cloud AWS & OpenStack:AWS Lambda, S3, EC2 EMR, RDS, Kinesis Firehose, Terraform, CloudWatch, Glue, API Gateway, Elastic/OpenSearch, EKS, ECS, Fargate Programming:Python 3, Java, JavaScript, Typescript, Go / Golang, SQL, Bash, Batch Infrastructure as Code (IaC): Terraform, Ansible, CloudFormation, AWS CDK Python Frameworks:React.js, Angular > 7, Next.js, Vue.js, Jest.js, REST APIs, Selenium, Webdriver.io, Jupyter Notebooks, GitHub Actions

Neural Networks:Tensorflow 2.X, Karas, AWS SageMaker, PyTorch, Sci-kit Learn, Deep Learning Machine Learning:Supervised Learning, Unsupervised Learning, RNN, KNN, CNN, SageMaker, NLP WORK EXPERIENCE

Senior AWS Cloud Engineer - BMO, Toronto, Ontario (remote, contract)03/2024 - present

● Developed AWS Cloud Development Kit (CDK) stacks in TypeScript to automate infrastructure provisioning, reducing environment setup time by 85%.

● Enhanced environment reliability by adopting Infrastructure as Code (IaC) best practices, implementing automated validations, ensuring full configuration parity, and eliminating deployment issues caused by environment drift.

● Configured and managed Amazon EKS clusters, optimizing VPC networking, IAM roles, and autoscaling node groups to improve geo availability, enhance security compliance, and reduce costs (FinOps) by 30% month to month.

● Optimized CI/CD pipelines, automating build and release processes to double deployment speed and improve efficiency.

● Reduced AWS SageMaker model release cycles by 2 days by integrating CodePipeline CI/CD with automated testing, ensuring model quality and faster delivery. Senior Software and SRE Engineer - Petco, San Diego, California (remote, contract)11/2022 - 02/2024

● Managed data migration using AWS Kinesis Firehose, achieving 100% real-time data sync from Django REST API to AWS S3.

● Accelerated AWS Lambda REST API development by 63% by building new endpoints via AWS API Gateway.

● Utilized Python CDK for AWS CloudWatch to establish robust monitoring systems, generating 11,000 log files.

● Engineered a unique Python solution for collecting and analyzing Prometheus metrics and logs, enabling proactive automation and communication via email and chats.

● Using Route 53 configured and maintained DNS settings for over 10 domains, utilizing latency-based routing to reduce latency by 30% and improve availability zone-specific application performance.

● Managed AWS Network Firewall rules to protect 23+ applications, reducing security incidents by 19% by implementing advanced traffic filtering and threat detection policies. BackEnd and SRE Engineer - RenderSEO, Orange County, California (remote, contract)01/2022 - 10/2022

● Designed and implemented an AWS EKS solution, accelerating the company's service migration by 2 months.

● Optimized script for API interaction and data synchronization, resulting in a 300-line truncation for enhanced script efficiency.

● Utilized JavaScript to develop backend infrastructure, delivering JWT token-protected information to clients 1.4 times faster.

● Created JavaScript-based Lambda functions in response to various AWS events, such as changes to data in an S3 bucket, updates to a DynamoDB table, and incoming messages in an SQS queue.

● Performed batch processing tasks for data cleansing and analysis by invoking Lambda functions on a scheduled basis using CloudWatch events.

Software Automation and Validation Engineer - Intel Corporation, Toronto, Ontario (contract) 06/2021 - 12/2021

● Designed and programmed Python plugins for automation, boosting team testing speed by 47.7%.

● Created a Python framework to simulate faults or errors in microprocessor behavior and to measure and analyze the power consumption of microprocessors under different workloads.

● Collaborated on Jira test item development, successfully resolving 100% of tickets related to various bugs through effective debugging over multiple weeks.

● Constructed a machine learning pipeline utilizing data to achieve a 76.82% accuracy in classifying various media items.

Web and Big Data Developer - freelance 02/2019 - 05/2021

● Leveraged the MERN stack to develop end-to-end websites, seamlessly integrating front-end and back-end functionalities.

● Enhanced website performance by strategically minimizing CSS and JavaScript code, resulting in a 14% improvement in site responsiveness.

● Utilized client data to generate insightful data charts, effectively enhancing user satisfaction by 6.97%. EDUCATION & CERTIFICATIONS

AWS Cloud Practitioner Certificate 2024

BrainStation Boot Camp Data Science Diploma 2021 University Of Toronto Statistics & Computer Science Scholar 2019-2021

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