Kostas Vasilopoulos

AI/ML Engineer @ Pfizer | Econ (Ph.D.)

Professional Summary

I am a Machine Learning Engineer with a Ph.D. in Economics, combining rigorous research methodology with hands-on experience building and operating production ML systems at scale. My background enables me to translate complex analytical and modeling challenges into robust, production-grade engineering solutions.

My focus is on enterprise ML platforms, with expertise in MLOps execution patterns, responsible AI, and horizontally scalable distributed systems. I work on integrating and scaling Large Language Models across enterprise environments, defining platform-wide standards for AI service integration, security, and lifecycle management in regulated settings.

Professional Experience

Pfizer

Machine Learning Engineer, Manager

May 2023 - Present
  • Technical owner for integrating and scaling **Large Language Models (LLMs)** across an enterprise platform serving **1,800+ users**, addressing reliability, performance, and compliance constraints
  • Defined and owned platform-wide standards for **AI service integration**, security, and lifecycle management across multiple teams
  • Established and enforced **MLOps** execution patterns for model deployment, monitoring, and access control in production
  • **Technical Lead for Ethicara ML**: Led the design and implementation of responsible and ethical AI solutions to align with enterprise and regulatory standards
  • Acted as a bridge between **users, system administrators, and engineering teams**, governing platform usage, onboarding, and operational processes at scale
  • Drove cross-team adoption of AI capabilities by defining reusable platform abstractions and reference implementations aligned with business needs

Key Technologies:

Python • Machine Learning • LLMs • MLOps • Kubernetes • Cloud Computing

SophoTree

Machine Learning Engineer

January 2022 - May 2023
  • **Tech Lead** for SophoTree's EU Horizon 2020 initiatives (**Infinitech, AI4PP**), owning end-to-end system architecture, delivery, and long-term technical direction
  • Owned the end-to-end ML lifecycle and defined reusable pipelines adopted across multiple models and teams
  • Designed and implemented a **distributed data collection and processing platform** on Kubernetes, horizontally scaling to support **millions of jobs per day**
  • Productionized multiple ML models with autoscaling, microbatching, and runtime optimizations, achieving a **320% increase in throughput** and a **40% reduction in infrastructure costs**
  • Built and operated API microservices integrating **PostgreSQL**, **Elasticsearch**, and analytics pipelines to support real-time and batch workloads
  • Acted as de facto **platform owner**, building and operating **API microservices** (**PostgreSQL**, **Elasticsearch**, analytics pipelines) and establishing CI/CD, observability, and reliability standards across services
  • Led development and deployment of production NLP pipelines using **Spark NLP** (classification, sentiment analysis, NER), later reused across document and news processing workloads

Key Technologies:

Python • Kubernetes • PostgreSQL • Elasticsearch • Machine Learning • Microservices • Spark NLP

Data Scientist

June 2021 - January 2022
  • Developed and trained NLP models for large-scale news and document analysis, focusing on **classification, sentiment analysis, and entity extraction**
  • Introduced advanced NLP techniques into the platform, expanding analytical capabilities beyond traditional structured data

Key Technologies:

Python • Data Analysis • Machine Learning • NLP • Statistics

Lancaster University

Visiting Researcher

July 2021 - July 2022
  • Designed and implemented real-time **exuberance detection and predictive modeling systems**, translating advanced econometric theory into production-grade software
  • Delivered **14–150× performance improvements** via optimized matrix inversion and numerical methods, enabling real-time processing of large-scale economic datasets
  • Work from the Housing Observatory featured in **The Times** and actively used by practitioners, including **Central Banks**

Key Technologies:

Data Analysis • Statistical Modeling • Research • Economics • Optimization

Teaching Associate

November 2020 - August 2021
  • Delivered undergraduate and postgraduate economics courses
  • Consistently received outstanding student evaluations

Key Technologies:

Teaching • Economics • Education

Research Assistant & Graduate Teaching Assistant

October 2016 - October 2020
  • Built analytical models and interactive tools for real-time monitoring of UK national and regional housing markets
  • Led web development of the Housing Observatory platform (https://housing-observatory.com/), collaborating with the **Federal Reserve Bank of Dallas**

Key Technologies:

Data Analysis • Statistical Modeling • Web Development • Economics

Education

Ph.D. in Economics

Lancaster University

2016-2020

M.Sc. in Economics, Applied Finance

University of Macedonia

2014-2016

B.Sc. in Economics

University of Macedonia

2009-2014

Technical Skills

Programming Languages

Python & R90%
SQL75%
JavaScript/TypeScript & HTML/CSS60%

Machine Learning & AI

Generative AI & LLMs90%
Natural Language Processing85%
Deep Learning & Neural Networks75%

Tools & Technologies

Docker & K8s85%
AWS Cloud Services85%
Git & CI/CD, DevOps80%