Kostas Vasilopoulos
AI/ML Engineer @ Pfizer | Econ (Ph.D.)
Specializing in enterprise ML platforms, MLOps execution, and responsible AI systems
About Me
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.
Core Expertise & Skills
AI & Machine Learning
- Generative AI & Large Language Models (RAG, embeddings, fine-tuning)
- Natural Language Processing & Text Analytics
- Production ML Operations & Model Lifecycle (model deployment, versioning, automated pipelines)
- Model Evaluation, Monitoring & Drift Detection
Engineering & Infra
- Programming: Python, R, SQL, JavaScript, C++
- Distributed Computing & Microservices Architecture (horizontally scalable systems, service-oriented architecture)
- Cloud & Containers: AWS, Azure, Docker, Kubernetes
- Scalability & Performance Optimization (throughput optimization, cost reduction, runtime efficiency)
- Web Development & REST APIs
- Data Engineering: ElasticSearch, Postgres, Kafka, NoSQL (search, storage, streaming)
- DevOps: Git, Linux, CI/CD Pipelines
Professional Experience
Pfizer
Machine Learning Engineer, Manager
- ▸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
SophoTree
Machine Learning Engineer
Promoted from Data Scientist (06.2021 -- 01.2022)
- ▸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
Data Scientist
- ▸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
Lancaster University
Visiting Researcher
- ▸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
Teaching Associate
- ▸Delivered undergraduate and postgraduate economics courses
- ▸Consistently received outstanding student evaluations
Research Assistant & Graduate Teaching Assistant
- ▸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
Education, Publications & Awards
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
Awards & Achievements
Departmental Studentship Award
Lancaster University
2016-2019
MSc Scholarship
University of Macedonia
Awarded based on academic excellence
Selected Publications
Exuber: Recursive Right-Tailed Unit Root Testing with R
Vasilopoulos, K., Pavlidis, E., & Martínez-García, E.
Journal of Statistical Software, 103, 1-26 (2022)
Speculative Bubbles in Segmented Markets: Evidence from Chinese Cross-Listed Stocks
Pavlidis, E.G., & Vasilopoulos, K.
Journal of International Money and Finance, 109, 102222 (2020)
Real Estate and Construction Sector Dynamics over the Business Cycle
Vasilopoulos, K., & Tayler, W.
Economica (accepted)
Thesis
Essays in Macroeconomics and Finance
PQDT-Global (2020)
Contact
I'm always open to discussing new projects, opportunities, or collaborations. Feel free to reach out through any of the following channels:
Let's Connect
Whether you want to discuss a project, ask about my experience, or just say hello, I'd love to hear from you.
Academic Work
Looking for my academic research and publications? Visit my academic website
(archived site, no longer maintained)