Leo Vaicer

Software Developer — GE Vernova, Barcelona, Spain

• Built and maintained the Python ecosystem behind wind resource assessment - SODAR (Sonic Detection and Ranging) and met-mast processing, vectorized in NumPy.
• Implemented detrending and temporal decomposition to analyze air-mass density stability and hub/mast positioning, feeding turbine siting decisions.
• Rewrote critical Airflow DAGs around vectorized algorithms: 5–10X faster task execution and far fewer pipeline failures.
• Migrated 4+ core services to Python 3.x, writing LLM-based static analysis to automate type-hinting, signature refactoring, and dependency resolution (UV/Ruff), and built pymolt to automate behavioral verification.
• Built the observability stack - Grafana, Loki, Prometheus — over GPU-accelerated Kubernetes clusters, cutting incident resolution time through real-time tracking.

Data Engineer — Trialing Health S.L., Barcelona, Spain

• Set up an AWS S3 data lake and rebuilt the Airflow ETL around it, cutting data-to-insight latency from 120 minutes to 40.
• Designed a multi-tier validation framework with a dedicated quarantine zone for manual verification, holding data integrity across engineering and data-management teams.
• Built an ingestion engine (Regex, Pydantic) that turned non-standardized scientific records into a high-fidelity schema, letting physicians track drug efficacy and treatment outcomes in real time.
• Deployed a unified medical data platform aggregating unstructured research archives from hundreds of hospitals and clinical centers across Spain and Portugal.

DevOps and MLOps — Lemay.ai, Toronto, Canada

• Administered bare-metal Proxmox hypervisors (LVM partition resizing, hardware allocation) alongside core AWS cloud infrastructure (EKS, EC2, S3).
• Implemented Apache Kafka & Kafka Streams for microservice event streaming, establishing baseline observability across event lifecycles.
• Designed a secure data ingestion layer enforcing strict Role-Based Access Control (RBAC) across dataset onboarding.
• Deployed self-hosted GitLab CI/CD pipelines and managed version-controlled Nginx reverse-proxy configurations.

Data & MLOps Engineer — Contract (DataArt, Inmost, Virtuace)

• Delivered infrastructure and ML work for international clients on cloud migration and high-load systems: disaster recovery on AWS to 99% availability, and 15–25% lower storage and processing costs through S3/Lambda resource optimization.
• Decoupled monolithic ML pipelines into modular microservices using MLflow, and integrated DVC (Data Version Control) for reproducible dataset and model tracking.
• Led on-premise to cloud migrations, optimized PostgreSQL aggregation schemas, and standardized CI/CD across client engineering teams.

Backend Engineer, ML Infrastructure — Sembly AI — full-time, concurrent with BSc studies, Odesa, Ukraine

• Architected a high-throughput Kafka audio ingestion system for real-time stream processing, driving a 30% improvement in system responsiveness.
• Decoupled monolithic AI platform into fault-tolerant microservices and overhauled the NLP inference path — slashing deployment latency by 40% and boosting inference speed by 25%.
• Established end-to-end automated model training and validation workflows, cutting model time-to-production by 50%.

R&D Engineer, Control & Energy Systems — Elliscope (co-founded) - part-time, concurrent with Sembly AI

R&D venture on autonomous high-altitude airships and hybrid energy propulsion. Presented at WebSummit 2021. https://elliscope.zeelex.me

• Developed adaptive control algorithms - Kalman filtering and Model Predictive Control - compensating for non-linear turbulence and buoyancy loss at 10–12 km, and assessed controllability across atmospheric profiles.
• Modeled hydrogen fuel-cell integration and energy balance for a theoretical 5+ week flight endurance, identifying the critical lift-to-weight constraints for zero-emission propulsion.
• Designed and tested scale-model demonstrators validating stability and sensor-integration hypotheses; published findings within the Ukrainian Space Association.

Graduate coursework — MSc in Modeling for Science and Engineering — Universitat Autònoma de Barcelona (UAB)

• Mathematical modeling, dynamical systems and complexity, high-performance computing (HPC)

BSc, Applied Mathematics and Computing — Odesa I.I.Mechnikov National University

• Numerical methods, optimization and control theory, machine learning, econometrics
• Completed while working full-time