Description

Full-Stack ML Engineer | Model Development to Production MLOps | 10hrs/week

I build ML solutions end-to-end: from developing models to deploying them in production at scale. Whether you need someone to architect your ML platform, develop custom models, or optimize existing systems, I handle the complete pipeline.

What I deliver:

Model Development & ML Engineering

Developed 20+ production models across computer vision, NLP, time-series forecasting, and GenAI
Built custom ML solutions for warehouse optimization, process automation, and forecasting
Designed and implemented RAG systems and LLM-based applications for enterprise use
Created vector embeddings pipelines and retrieval systems for semantic search

MLOps & Production Infrastructure

Built MLOps platforms managing full model lifecycle from training to deployment
Optimized serving infrastructure, reducing costs through efficient GPU utilization
Implemented automated CI/CD pipelines for model training, deployment, and monitoring (Dagster, MLflow, Comet ML)
Deployed serverless model endpoints and real-time inference APIs

Data Engineering & Architecture

Architected cloud data infrastructure managing relational and vector databases for AI workloads
Built data pipelines processing large-scale unstructured data for ML applications
Led data strategy and collection frameworks across engineering teams

I'm best suited for:

Startups needing ML capabilities from scratch (model development + infrastructure)

Companies wanting to improve existing ML models or deploy new ones

Teams building GenAI/RAG systems, computer vision, or forecasting solutions

Optimizing ML systems for performance and cost

Available for 10 hours/week. I work independently, own problems end-to-end, and deliver production-ready solutions.

Languages

English
Native or bilingual

Workplace preferences

Remote only

Primarily works remotely

carVertical
Senior Machine Learning Engineer
August 2024 - Today (1 year and 10 months)
Kaunas, Kaunas City Municipality, Lithuania
• Optimized ML serving infrastructure to process 6M daily with vision and NLP models, improving GPU utilization and reducing costs through pipeline optimization and model reuse across services
• Built and maintain MLOps platform managing full model lifecycle for multiple cross-functional teams
• Deployed 20+ production models with automated CI/CD pipelines for training, deployment, and monitoring
NLP Computer Vision FastAPI
INTUS Windows LT
AI Engineer
September 2023 - August 2024 (11 months)
Šiauliai, Šiauliai City Municipality, Lithuania
• Built end-to-end RAG systems processing large-scale unstructured data for production GenAI applications
• Architected cloud-based data infrastructure managing relational and vector databases for AI workloads
• Developed vector embeddings pipeline and retrieval systems for enterprise RAG implementations
• Designed and implemented LLM and computer vision solutions for warehouse and process optimization tasks
• Led data strategy and collection frameworks across engineering teams
Computer Vision / Image Processing ETL (Extract, Transform, Load) Processes RAG LLM Data science
A Danish client
Data Scientist (Freelancing)
February 2024 - June 2024 (4 months)
Denmark
• Built and optimized ML time-series forecasting models
• Implemented automated training pipelines using Dagster and Comet ML for experiment tracking and versioning
• Delivered end-to-end MLOps solution from model training to serverless model deployment
MLOps Model Optimization Time-series forecasting