Machine Learning + Data + Systems Engineer
Aris Vlasakakis
Reliable ML systems for real-world scale.
You get product-ready inference, dependable data pipelines, and pragmatic engineering practices that raise velocity without trading reliability. I favor functional programming because testability is a core requirement for how I design systems.
About
You’re working with a hands-on engineer focused on measurable outcomes: reliability, cost, and velocity. I build ML systems that support $1M+ in daily revenue and keep teams shipping safely.
Principles
Impact Snapshot
-90%
Inference infra cost after moving to Triton.
-75%
Sev 0 incidents with testing hardening.
+40%
Team velocity after modernizing practices.
$1M+
Daily revenue supported by ML systems.
Core Expertise
ML Engineering
- Inference systems with Triton and custom serving layers
- Model testing infrastructure and reliability guardrails
- Open-source LLM integration and deployment
- Batch recommender systems at massive scale
Data Engineering
- Large-scale learning pipelines in SparkML
- Batch recommender pipelines in Dataflow
- Streaming dataflows and Kafka-driven systems
- Airflow migration and orchestration modernization
Software Engineering
- Composable architectures with Scala + Python
- Performance, latency, and cost optimization
- Team enablement and sustainable delivery
Selected Work
Large-Scale Learning on SparkML
Built distributed training pipelines to improve throughput and model iteration speed.
Stack: SparkML · Scala · Python
Batch Recommender Systems
Built user-product recommenders for tens of millions of users and billions of items.
Stack: Dataflow · TensorFlow · PMML
Inference Migration to NVIDIA Triton
Replatformed serving to reduce latency and cut infra costs by 90%.
Stack: Triton · Docker · Monitoring
Inference Testing Infrastructure
Designed reliability tests that dropped Sev 0 incidents by 75%.
Stack: CI/CD · Python · Observability
Modernized Model Orchestration
Upgraded orchestration to accelerate releases and enable LLM workflows.
Stack: Airflow · Workflow Orchestration · LLMs
Systems & Stack
Working Style
You get a pragmatic builder who obsesses over reliability, clear contracts, and measurable outcomes. Systems ship with observability, tests, and an upgrade path baked in.
Aris Vlasakakis
Machine Learning + Data + Systems Engineer
Let’s Build Something Durable
Reach out for ML systems, data platforms, or reliability-focused engineering leadership.