grammarly fixes for en version

cv_en.tex

@@ -58,33 +58,33 @@
 3 connected projects in one big department with overlapping engineering teams.
 \begin{enumerate}
 \item Worked on architecture and MVP for Visper.tech.
-\item Integrated abandoned ML-solution for video generation to Visper.tech backend.
+\item Integrated abandoned ML solution for video generation to Visper.tech backend.
-\item Created and launched widget backend with complex architecture and Python/Golang components. $\geq$ 500k active devices each day and $\geq$ 10k RPS average.
+\item Created and launched a widget backend with complex architecture and Python/Golang components. $\geq$ 500k active devices each day and $\geq$ 10k RPS average.
 \item Led backend development for news and widget including architecture and tech communications with other teams.
 \end{enumerate}
 \textbf{Stack:} Golang, Python, Django + FastAPI, Postgres, RabbitMQ, Redis/KeyDB, Prometheus + Grafana, Traefik, GitLab CI, Sentry, Docker.
 }
 
 \cventry{Mar 2018 -- Jun 2020}{Python Developer}{\textsc{Kvint}}{Moscow (remote work)}{}{
-Platform for e2e robot calls with call state (we used FSM)
+The platform for e2e robot calls with call state (we used FSM)
-and external API calls during call.
+and external API calls during them.
-High scalability and no-code approach for most of functions.
+High scalability and no-code approach for most of the functions.
 \begin{enumerate}
 \item Worked on core FSM part, integrated Lua scripting and testing concepts with coverage monitoring.
-\item Created from scratch in-place replacement for main dialing component, up to 100 simultaneous calls on each server and millions of calls each month.
+\item Created from scratch in-place replacement for the main dialing component, up to 100 simultaneous calls on each server and millions of calls each month.
 \item Was responsible for integration with custom STT (Speech-to-Text) library on CUDA cores. Used C++ for near-zero overhead.
-\item Created scalable and fault-tolerant services architecture for most of backend tasks.
+\item Created scalable and fault-tolerant services architecture for most of the backend tasks.
 \item Integrated custom VAD (Voice Activity Detector) with Websockets, about 80\% STT load reduction.
-\item Integrated ML pipeline for NLU with custom dictionary and data for each client. Used Google Compute with dynamic instances for about 95\% training cost reduction.
+\item Integrated ML pipeline for NLU with a custom dictionary and data for each client. Used Google Compute with dynamic instances for about 95\% training cost reduction.
 \end{enumerate}
 \textbf{Stack:} Python + pytransitions for FSM, Websockets, Lua for scenario scripts, C++, Asterisk, MongoDB, MySQL, RabbitMQ, Docker.
 }
 
-\cventry{Jul 2017 -- Feb 2018}{Python Developer}{\textsc{Krista}}{Moscow}{}{Telegram chat bot for open data that can understand queries in natural language.
+\cventry{Jul 2017 -- Feb 2018}{Python Developer}{\textsc{Krista}}{Moscow}{}{Telegram chatbot for open data that can understand queries in natural language.
 \begin{enumerate}
-\item Integrated code metrics + static code analysis as part of CI process.
+\item Integrated code metrics + static code analysis as part of the CI process.
 \item Redesigned data process to get measurable results for each commit.
-\item Reimplemented queries building process to ML-approach with big step up in performance from about 80\% to 98\% on test data.
+\item Reimplemented queries building process to ML-approach with a big step up in performance from about 80\% to 98\% on test data.
 \item Managed tech debt reduction process.
 \end{enumerate}
 \textbf{Stack:} Python3 + scikit-learn for ML, Apache Solr, Telegram API.