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I am an AI/ML engineer with a decade of experience turning research concepts into production products across healthcare, voice technology, and EdTech. I specialize in agentic systems, retrieval-augmented generation, language models, deep learning, cloud platforms, and scalable API-driven applications. I enjoy working closely with domain experts and lean engineering teams to move products from MVP to production. My experience includes HIPAA-compliant healthcare analytics, multimodal voice bots, adaptive tutoring applications, cloud infrastructure, model evaluation, and reusable engineering playbooks that improve delivery and onboarding.…I am an AI/ML engineer with a decade of experience turning research concepts into production products across healthcare, voice technology, and EdTech. I specialize in agentic systems, retrieval-augmented generation, language models, deep learning, cloud platforms, and scalable API-driven applications. I enjoy working closely with domain experts and lean engineering teams to move products from MVP to production. My experience includes HIPAA-compliant healthcare analytics, multimodal voice bots, adaptive tutoring applications, cloud infrastructure, model evaluation, and reusable engineering playbooks that improve delivery and onboarding.

Lukas Lebenko

AI Engineer, Software Engineer, Data Scientist, +3

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I am an AI/ML engineer with a decade of experience turning research concepts into production products across healthcare, voice technology, and EdTech. I specialize in agentic systems, retrieval-augmented generation, language models, deep learning, cloud platforms, and scalable API-driven applications. I enjoy working closely with domain experts and lean engineering teams to move products from MVP to production. My experience includes HIPAA-compliant healthcare analytics, multimodal voice bots, adaptive tutoring applications, cloud infrastructure, model evaluation, and reusable engineering playbooks that improve delivery and onboarding.…I am an AI/ML engineer with a decade of experience turning research concepts into production products across healthcare, voice technology, and EdTech. I specialize in agentic systems, retrieval-augmented generation, language models, deep learning, cloud platforms, and scalable API-driven applications. I enjoy working closely with domain experts and lean engineering teams to move products from MVP to production. My experience includes HIPAA-compliant healthcare analytics, multimodal voice bots, adaptive tutoring applications, cloud infrastructure, model evaluation, and reusable engineering playbooks that improve delivery and onboarding.

Available to hire

I am an AI/ML engineer with a decade of experience turning research concepts into production products across healthcare, voice technology, and EdTech. I specialize in agentic systems, retrieval-augmented generation, language models, deep learning, cloud platforms, and scalable API-driven applications.

I enjoy working closely with domain experts and lean engineering teams to move products from MVP to production. My experience includes HIPAA-compliant healthcare analytics, multimodal voice bots, adaptive tutoring applications, cloud infrastructure, model evaluation, and reusable engineering playbooks that improve delivery and onboarding.

Skills

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Intermediate

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Intermediate

Work Experience

AI/ML Engineer at SUPER HOW

March 1, 2024 - July 1, 2026

Designed an agentic analytics platform using LangChain, GPT-4, multimodal retrieval, clinical knowledge graphs, vector search, and rule-based validation to surface biomarkers and extract signals from imaging, omics, and EHR data. Built clinician-facing differential-diagnosis workflows with FastAPI and HIPAA-focused security controls. Applied weak supervision, Scikit-Learn, and XGBoost to cancer imaging and RNA-seq risk modeling. Containerized and deployed multi-GPU training and inference pipelines using Docker, PyTorch, DeepSpeed, Hugging Face Transformers, Kubernetes, AWS EC2, S3, SageMaker, and Bedrock. Created evaluation harnesses for hallucination and bias testing, secure data-lake policies with AWS Lake Formation, and reusable notebooks and API templates for researchers.

AI Software Engineer at Ailancer

March 1, 2020 - February 1, 2024

Built the company’s AI consulting practice and delivered production solutions on AWS SageMaker and Amazon Bedrock, contributing to AWS Generative AI Competency. Developed RAG systems with LangChain, LangGraph, LlamaIndex, OpenSearch, and FastAPI for voice bots, speech analytics, and language-learning applications. Created Leya AI, a speech-driven English-learning product combining ASR, GPT-4 dialog, and gamified vocabulary. Built outbound voice bots and streaming ETL and vector-database pipelines, using Kubernetes, AWS Lambda, Terraform, and GitHub Actions. Improved inference throughput with DeepSpeed and Triton-backed GPU autoscaling, achieving global latency below 200 ms. Established onboarding playbooks and full-stack observability with OpenTelemetry and Prometheus/Grafana.

Machine Learning Engineer at SciForce

April 1, 2018 - February 1, 2020

Productionized a high-accuracy NER pipeline using spaCy, NLTK, and Scikit-Learn for curriculum tagging. Prototyped a classroom-engagement analyzer using OpenCV, TensorFlow, and Keras to track student attention from smart-camera streams. Integrated Google Cloud AutoML for text-classification experiments and built scalable PySpark and Python ETL pipelines for legal and educational documents. Created a Java and Spring Boot REST framework for training and serving clustering and NER models, containerized with Docker. Deployed TensorFlow Serving on Kubernetes for near-real-time EdTech feedback, developed GDPR-compliant data-governance policies, and mentored junior engineers in CI/CD, Git, and testing.

Python Engineer at Kinfirm

July 1, 2014 - March 1, 2018

Delivered accessible clinician-facing web applications using React, MobX, Material-UI, and Node.js for hospital workflows. Built HIPAA-ready REST APIs with Express, Sequelize, PostgreSQL, and JWT, including audit trails and zero-trust security patterns. Established Azure DevOps CI/CD pipelines, managed services with PM2, and configured NGINX reverse proxies. Containerized deployments with Docker and orchestrated Kubernetes clusters. Developed patient-risk scoring models and medical chatbots with TensorFlow, PyTorch, Flask, and DrQA, later refactoring them to RAG architectures using FastAPI and AWS. Implemented Terraform infrastructure and database migrations and conducted clinician demonstrations and onboarding workshops.