Professional Overview
ML/MLOps engineer shipping production voice AI infrastructure: self hosted ASR and TTS pipelines at sub 200ms p50 latency, deployed solo on bare metal Kubernetes with GPU backed inference. Comfortable owning a system end to end, from model serving to concurrency tuning to production benchmarking.
Areas of Expertise
AI & Machine Learning Engineers
Design, train, and ship production ML models — from data pipelines to model inference at scale. Covers supervised learning, neural networks, LLM integration, and model optimisation.
MLOps & AI Infrastructure
Architect scalable ML infrastructure — CI/CD for ML, model versioning, experiment tracking, monitoring, and cloud deployment on AWS, GCP, or Azure.
Open to
Full-time
AI Expertise
Skills
Experience Level
Mid-Level
Current location
India
Time Zone
Tallinn UTC+2
Primary Work Language
English
