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% HEADER
\begin{center}
{\LARGE \textbf{Pavel Vasilyev}}\\[4pt]
{\large LLM Engineer / AI Infrastructure Specialist}\\[8pt]
Jerusalem, Israel $\cdot$ marchdown@gmail.com $\cdot$ +972-54-343-1123\\
\href{https://github.com/marchdown}{marchdown} $\cdot$
\href{https://linkedin.com/in/pavel-vasilyev-65105b149}{pavel-vasilyev-65105b149}
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\vspace{12pt}

% SUMMARY
\section*{Summary}
LLM engineer with 14 years ML/NLP experience and 3 years specializing in production language model systems.

Expert in LLM workflows, safety guardrails, prompt engineering, and scaling generative AI infrastructure.

Strong functional programming background (Clojure, Elixir) with production systems experience in Python, Rust, Go, Java, and R.

MSc Computational Linguistics, BSc Nuclear Physics.


% EXPERIENCE
\section*{Experience}

\subsection*{Independent Consultant}
\textbf{Various Clients} \hfill Mar 2024 – Dec 2024\\
Remote

\begin{itemize}[itemsep=2pt]
\item **LevEhat NGO (CTO, 5 months):** Led cloud migration from GCP to AWS, coordinated team of 5 for volunteer management platform
\item **Fintilligence (Technical Lead, 4 months):** Built market microstructure analytics platform with PIN/VPIN algorithms and Level 2 data pipelines
\item **General consulting:** Time-series forecasting models, NLP classification systems, infrastructure architecture
\end{itemize}


\subsection*{AI Architect}
\textbf{Stamina AI} \hfill Jan 2023 – Dec 2023\\
Remote

\begin{itemize}[itemsep=2pt]
\item Built complete LLM pipeline: prompt engineering, context management, response generation, safety guardrails
\item Integrated OpenAI GPT-3.5/4 APIs with custom safety layers and content filtering
\item Designed conversation state management and session handling for therapeutic context
\item Set up production infrastructure: API gateway, load balancing, monitoring, logging
\item Coordinated with consulting psychotherapists to ensure clinical appropriateness of responses
\item Implemented usage analytics and conversation quality monitoring dashboards
\end{itemize}


\subsection*{Independent Consultant}
\textbf{Various Clients} \hfill 2022 – 2023\\
Remote

\begin{itemize}[itemsep=2pt]
\item Projects: time-series forecasting, text classification, data pipeline optimization
\end{itemize}


\subsection*{Senior Researcher}
\textbf{Spring Research} \hfill 2020 – 2021\\
Remote

\begin{itemize}[itemsep=2pt]
\item Developed ML models for trading signal generation using time-series analysis and statistical methods
\item Built data pipelines processing Level 2 market data (tick-by-tick, order book, market depth)
\item Researched topology-inspired approaches to market microstructure modeling
\item Implemented backtesting infrastructure for strategy evaluation
\end{itemize}


\subsection*{Data Scientist}
\textbf{Nestlogic} \hfill 2019\\
Remote

\begin{itemize}[itemsep=2pt]
\item Built computer vision models for advertising creative optimization (image feature extraction)
\item Implemented A/B testing infrastructure using statistical hypothesis testing (t-tests, chi-square)
\item Deployed ML models to production on Google Cloud Platform with Kubernetes
\item Developed analytics dashboards tracking model performance and business KPIs
\end{itemize}


\subsection*{Data Scientist}
\textbf{Maverick Medical AI} \hfill 2018\\
Remote

\begin{itemize}[itemsep=2pt]
\item Developed NLP system for medical named entity recognition in clinical text using spaCy and BiLSTM
\item Built medical ontology framework for standardizing terminology across different hospital systems
\item Created decision support tools for clinical workflows highlighting critical findings
\item Worked within HIPAA compliance requirements for healthcare data
\end{itemize}


\subsection*{Full-Stack Engineer}
\textbf{Athena Portfolio Solutions} \hfill 2017\\
Remote

\begin{itemize}[itemsep=2pt]
\item Developed Java backend services for data processing and entity recognition
\item Implemented entity linking system connecting market events to portfolio positions
\item Built sentiment analysis models for earnings calls and analyst reports
\item Created knowledge graph of financial entities (companies, people, events, relationships)
\end{itemize}


\subsection*{Independent Tutor \& Consultant}
\textbf{Private Practice} \hfill 2016 – 2017\\
Remote / International Relocation

\begin{itemize}[itemsep=2pt]
\item Mathematics, statistics, programming, and computational linguistics instruction
\item ML/NLP consulting for various clients
\end{itemize}


\subsection*{Technical Tutor}
\textbf{Private Practice} \hfill 2017 – Present\\
Remote

\begin{itemize}[itemsep=2pt]
\item Students: high school through graduate level, plus professional colleagues
\item Peak activity during 2020 pandemic period
\end{itemize}

% EDUCATION
\section*{Education}

\subsection*{MSc Computational Linguistics}
\textbf{Russian State University for the Humanities (RSUH)} \hfill 2016\\
Moscow, Russia

\textit{Statistical NLP, Machine Translation, Information Extraction}


\subsection*{BSc Nuclear Physics}
\textbf{Czech Technical University} \hfill 2011\\
Prague, Czech Republic

\textit{Mathematical Modeling, Statistical Analysis, Computational Physics}

% SKILLS
\section*{Technical Skills}

\subsection*{LLM Engineering}
\textit{3 years production}

\textbf{APIs:} OpenAI GPT-3.5/4, Anthropic Claude\\
\textbf{Workflows:} prompt engineering, RAG pipelines, context management, safety guardrails, content filtering\\
\textbf{Infrastructure:} production deployment, latency optimization, monitoring, cost optimization\\
\textbf{Specialization:} therapeutic chatbots, conversational AI, safety systems\\


\subsection*{Programming}
\begin{itemize}[itemsep=2pt]
\item Python (10+ years production)
\item Clojure (10+ years)
\item Rust (5+ years)
\item Go (3+ years)
\item Elixir (2+ years)
\item Java, R, SQL (advanced), bash
\item Functional background: Common Lisp, Haskell
\end{itemize}


\subsection*{ML/AI}
\begin{itemize}[itemsep=2pt]
\item Frameworks: PyTorch, TensorFlow, Keras, scikit-learn, XGBoost, LightGBM, CatBoost
\item NLP: spaCy, NLTK, Hugging Face Transformers
\item Deep Learning: CNNs, RNNs, LSTMs, GRUs, Transformers, attention mechanisms, transfer learning, fine-tuning
\end{itemize}


\subsection*{Cloud \& Infrastructure}
\begin{itemize}[itemsep=2pt]
\item AWS: EC2, S3, SageMaker, Lambda
\item GCP: GCE, GCS, GKE
\item Containers: Docker, Kubernetes
\end{itemize}


\subsection*{Databases}
\begin{itemize}[itemsep=2pt]
\item PostgreSQL (expert)
\item MongoDB, Redis, Neo4j, SQLite, MySQL
\end{itemize}


\subsection*{Data Engineering}
\begin{itemize}[itemsep=2pt]
\item Apache Spark, Apache Airflow, Kafka
\item ETL pipelines, data quality, orchestration
\end{itemize}


\subsection*{Web \& APIs}
\begin{itemize}[itemsep=2pt]
\item Flask, FastAPI, Django
\item REST APIs, microservices architecture
\end{itemize}


\subsection*{DevOps}
\begin{itemize}[itemsep=2pt]
\item git, Linux, CI/CD (GitHub Actions, Jenkins)
\item Monitoring, logging
\end{itemize}


\subsection*{Domain Expertise}
\textbf{LLM Production Systems} \hfill \textit{3 years $\cdot$ }\\
Therapeutic chatbots, safety systems, prompt engineering, RAG pipelines

\textbf{Quantitative Finance} \hfill \textit{2+ years $\cdot$ }\\
Level 2 market data, PIN/VPIN algorithms, order flow analysis, backtesting

\textbf{Healthcare AI} \hfill \textit{1 year $\cdot$ }\\
Medical NER, clinical terminology, HIPAA compliance, decision support tools

\textbf{Financial NLP} \hfill \textit{1 year $\cdot$ }\\
SEC filings analysis, knowledge graphs, entity linking, sentiment analysis

% LANGUAGES
\section*{Languages}
English (Fluent), Russian (Native), French (Conversational), German (Conversational), Czech (Conversational), Hebrew (Basic)

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