Alexey Fateev | MLOps | LLMOps Engineer

SUMMARY

MLOps Engineer focused on building robust machine learning infrastructure and implementing DevOps practices in ML processes. Specialize in developing and optimizing pipelines for model training and deployment, implementing GitOps approaches using ArgoCD and FluxCD, automating ML processes. Experienced in working with high-load systems and deploying LLM solutions. Passionate about creating efficient ML infrastructure and constantly exploring new approaches to optimize MLOps processes. Driven to innovate in the field of ML systems automation and scaling.

EXPERIENCE

Team Lead MLOps | LLMOps Engineer

KTS at AlfaBank Project (Alfa Advanced Analytics Department)
August 2024 - Present, Russia

In this role, I lead the MLOps team in a project to create a unified RAG platform for the entire bank. My work combines technical leadership, model optimization, and interaction with business stakeholders to integrate new solutions.

Key Achievements:

  • Led a team (Data Scientists, Data Engineers, ML Engineers) as Tech Lead/Team Lead, successfully designing and implementing a unified RAG (Retrieval-Augmented Generation) platform across the entire bank
  • Optimized LLM model inference, resulting in a 40% performance improvement. This reduced the response time of the entire RAG service by half
  • Ensured high performance and reliability of the service, maintaining SLA at 5 seconds under load of up to 250,000 requests per day
  • Developed and implemented production-ready MLOps pipelines for LLM model deployment using KServe and vLLM
  • Resolved infrastructure constraints by building vLLM from source with flash-attention support for legacy CUDA (11.8)
  • Implemented a unified gateway (HiGress) for all LLM models and MCP (Model Context Protocol), centralizing management and access

Core Responsibilities:

  • Designing architecture and participating in RAG system implementation
  • Deploying and maintaining LLM inference infrastructure in new clusters based on KServe, including troubleshooting kNative and Istio components
  • Client interaction: conducting meetings, developing connection schemes for new clients to RAG service, and effort estimation
  • Creating unified pipelines for deploying various non-model services across multiple environments (clusters), improving release speed and consistency
  • Research and implementation of best practices for optimizing and accelerating LLM model inference
Tech Stack: Kubernetes, KServe, vLLM, RAG, ArgoCD, Istio, Python, Jenkins

MLOps Engineer

May 2023 - August 2024 · 1 year 4 months, Russia
  • Developed and maintained a machine learning model deployment platform, managing 100+ ML models as part of a specialized ML team
  • Orchestrated database operations, including table creation and structure optimization for enhanced performance
  • Led critical aspects of a large-scale infrastructure migration, including server relocation and system upgrades
  • Authored and implemented Lua scripts for Tarantool Cartridge cluster during application migration
  • Enhanced a Golang-based database emulator for Clickhouse, improving integration testing capabilities
  • Streamlined Python environment migration through RPM packaging and GitLab CI pipeline development
  • Developed and deployed a chat-bot application utilizing OpenAI API, Langchain, and RAG for custom report generation
  • Deployed applications in Kubernetes (k8s) environments, ensuring scalability and efficient container orchestration
  • Utilized Puppet for automated server deployment and configuration management
Tech Stack: Python, RAG, Lua, Golang, Clickhouse, Python, RPM, GitLab CI, OpenAI API, Langchain, Kubernetes, Puppet

Data Engineer

March 2022 - May 2023 · 1 year 3 months, Russia
  • DWH maintenance
  • Modeling new database objects from non-relational to relational form
  • Implementing Grafana and Prometheus to track metrics about DAGs execution
  • Creating and maintaining ETL pipelines to automate CRM interactions with customers through various communication channels (email, SMS, push notifications, etc)
  • Using asynchrony to speed up query execution
  • API integration with external systems
Tech Stack: Python, DWH, Apache Airflow, Apache Kafka, PostgreSQL

Data Engineer

August 2021 - March 2022 · 8 months, Russia
  • Developed data pipelines in GCP for financial data processing, including encryption and anonymization in PCI environment
  • Built backend services using FastAPI and deployed them to Cloud Run and Cloud Functions
  • Created and maintained data analytics protocols, standards and documentation
  • Developed web application using Django and Plotly Dash for IT job market trend analysis
  • Implemented ETL pipelines using Apache Airflow for data processing
  • Worked with technologies: GKE, Cloud PubSub, BigQuery, Cloud Build, PostgreSQL, Docker, Redis
Tech Stack: GCP, FastAPI, Django, Plotly Dash, Apache Airflow, GKE, Cloud PubSub, BigQuery, PostgreSQL, Docker, Redis

EDUCATION

Master of Mathematical Modeling and Computer Science

Voronezh State University
2009 - 2015, Russia