Serhei V. — Team Lead AI Engineer

Expertise in AI and Machine Learning (9.5 yr.), DevOps (2.5 yr.).

Last verified on September, 2025

Core Skills

Google PageSpeed Insights

TensorFlow

5 yr.

Bio Summary

Software Engineer with over 5 years of AI implementation experience, possessing deep expertise in machine learning and natural language processing. Proven track record in developing AI strategies, implementing automated document workflows, and training teams in AI tool adoption. Proficient in a range of technologies including AWS, Azure, Docker, Kubernetes, and various machine learning libraries (TensorFlow, PyTorch, Scikit-learn). Strong background in DevOps with experience setting up CI/CD pipelines and database administration, paired with the ability to produce precise technical documentation. Notably contributed to improved forecasting and customer service through predictive modeling. Holds a Master's degree in Project Management, reinforcing a solid foundation in both the practical and theoretical aspects of technology and project execution.

Technical Skills

AI & Machine Learning	Amazon Machine learning services, AWS ML (Amazon Machine learning services), AWS SageMaker, AWS SageMaker (Amazon SageMaker), BERT, GPT, LLaMA, Mlflow, TensorFlow, TensorFlow Serving, Whisper
.NET Platform	Azure
Python Frameworks	FastAPI
JavaScript Libraries and Tools	Immutable.js
Python Libraries and Tools	TensorFlow
Data Analysis and Visualization Technologies	k-NN
Databases & Management Systems / ORM	Microsoft Azure SQL Server
Cloud Platforms, Services & Computing	AWS, Azure
Amazon Web Services	AWS CloudWatch, AWS ML (Amazon Machine learning services), AWS S3, AWS SageMaker, AWS SageMaker (Amazon SageMaker)
Azure Cloud Services	Azure Blob Storage, Azure Monitor, Azure VM, Microsoft Azure SQL Server
Google Cloud Platform	Google Docs
Logging and Monitoring	Azure Monitor, Prometheus
SDK / API and Integrations	FastAPI
Message/Queue/Task Brokers	Kafka
Other Technical Skills	Illustration and icons, Palm OS, Python Requests Library, Qdrant, RDS, Weaviate

Work Experience

Team Lead AI Engineer, AI Strategy and Document Workflow Automation

Duration: 03/2021 to 01/2025
Summary: Developed the company's AI strategy and implementation roadmap, identifying automation opportunities using AI tools and implementing machine learning models for document workflow automation.
Responsibilities: Managed infrastructure and ensured high availability, established monitoring solutions, conducted on-call shifts, provided database administration, administered office laptops, and wrote technical documentation to share knowledge.
Technologies: Machine learning working libraries (DeepSpeed, TensorFlow, PyTorch, LangChain, Scikit-learn, Auto-GPT), Virtualization (Kubernetes, AKS, AWS Lambda, Docker), CI/CD (GitHub Actions, GitLab CI/CD, AWS CDK, CloudFormation, Azure DevOps), Databases (AWS RDS, Azure SQL, S3, Blob Storage, Amazon OpenSearch), APIs (FastAPI, AWS SageMaker Endpoints, Azure Machine Learning Endpoints), Machine learning models (GPT-2, LLaMA, PaLM 2, BERT, Whisper), Model serving (AWS SageMaker, AWS Bedrock, Azure ML), Monitoring (Prometheus, Grafana, MLflow, AWS CloudWatch, Azure Monitor)

Machine Learning Engineer, AI Solutions Integration and Optimization

Duration: 08/2015 to 02/2021
Summary: Led AI solutions integration across multiple company departments, selecting and implementing cloud-based machine learning platforms and automating data analysis to build predictive models for improved customer service response.
Responsibilities: Managed infrastructure and ensured high availability, established monitoring solutions, conducted on-call shifts, provided database administration, administered office laptops, and wrote technical documentation to share knowledge.
Technologies: Machine learning working libraries (TensorFlow, PyTorch, Scikit-learn), Cloud platforms (AWS, Azure), Automation scripting (Python), Databases (AWS RDS, Azure SQL, Kafka), APIs (FastAPI, AWS SageMaker Endpoints), Machine learning models (BERT, Stable Diffusion)

DevOps Engineer, Infrastructure Automation and Optimization

Duration: 11/2013 to 07/2015
Summary: Worked on automating and optimizing infrastructure operations through the use of modern DevOps practices and tools to foster high availability and efficient monitoring solutions.
Responsibilities: Managed infrastructure and ensured high availability, established monitoring solutions, conducted on-call shifts, provided database administration, administered office laptops, and wrote technical documentation to share knowledge.
Technologies: Virtualization (Kubernetes, AWS Lambda, Docker), CI/CD (Helm, GitHub Actions, GitLab CI/CD, AWS CDK, CloudFormation), Databases (AWS S3, Azure Blob Storage), Monitoring (Prometheus, Grafana, AWS CloudWatch, Azure Monitor)

Education

Project Management Master’s
Ukrainian national university
Not Provided

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