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Michael Kaesler

@michaelkaesler

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Senior Machine Learning Engineer specializing in production ML, LLMs, RAG, and medical AI with scalable impact.

United States

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What I'm looking for

I seek roles where I can lead end-to-end ML product delivery—building scalable LLM, retrieval, personalization, or medical AI systems with strong cross-functional collaboration and clear business or clinical impact.

I am a Senior Machine Learning Engineer with 8+ years shipping production ML systems across LLMs, RAG, knowledge graphs, recommendation systems, medical computer vision, and speech/NLP. I take end-to-end ownership from problem formulation through deployment and experimentation in high-stakes production environments.

I have built cost-efficient Generative AI systems, low-latency personalization and search models, and FDA-cleared medical AI that power millions of daily inferences, leveraging PyTorch, LLM fine-tuning, retrieval architectures, and production ML infrastructure like Kubernetes and AWS. Notable achievements include a 10× cost reduction and 5× speedup for a product knowledge graph, 25% lift in search-to-checkout conversion from a two-tower personalization model, and FDA 510(k) contributions for ultrasound AI.

I am known for translating ambiguous problems into reliable, scalable ML solutions with measurable business impact, designing robust MLOps and inference pipelines, and shipping low-latency services using Go/Kotlin backends. I collaborate closely with product and clinical partners to validate solutions through A/B testing and regulatory-grade documentation.

Experience

Work history, roles, and key accomplishments

Current

Senior Machine Learning Engineer

Current

DoorDash

Jul 2024 - Present (1 year 6 months)

Built LLM-powered Product Knowledge Graph and hierarchical RAG systems, achieving 10× cost reduction, 5× speedup, and 92%+ accuracy across millions of SKUs while improving search-to-checkout conversion by 25%.

LLM RAG Faiss PyTorch Embeddings Kubernetes Go A B Testing

Sr. Deep Learning Engineer

EXO

Jun 2020 - Oct 2023 (3 years 4 months)

Architected end-to-end FDA-cleared ultrasound AI pipeline using 3D CNNs on 2M+ studies, delivering <5% MAE for ejection fraction and Dice >0.92 for LV segmentation while reducing iteration time 40%.

PyTorch U Net Onnx TensorRT MLOps MLFlow DVC Medical Imaging

Deep Learning Engineer

DialogTech

Feb 2018 - Jun 2020 (2 years 4 months)

Built production ASR and multi-task NLP pipelines processing 10M+ monthly calls, achieving <15% WER and enabling real-time sentiment tracking that increased sales conversion by 12%.

Kaldi BiLSTM CRF Go Kubernetes NLP

Graduate Student Consultant

Kavi Global

Sep 2017 - Dec 2017 (3 months)

Implemented Faster R-CNN and tracking pipelines to detect 19 surgical markers in medical video, enabling real-time computer-assisted surgery with robust temporal consistency.

Object Detection Kalman Filter Transfer Learning Trackings

Member of Technical Staff Intern

The Aerospace Corporation

Jun 2017 - Aug 2017 (2 months)

Trained VGG-16 CNN to filter false detections in satellite imagery, reducing false positives by 65% and accelerating analyst review cycles by 65% through automated filtering.

CNN Transfer Learning Image Processing Precision Recall Evaluation

Data Science Intern

Ecolab

Jun 2016 - Aug 2016 (2 months)

Built a Random Forest fuzzy entity resolution system linking lab data with IoT streams achieving 87% accuracy and supported predictive models across 40,000+ systems generating large-scale telemetry.

Random Forest Time Series TF IDF Cross Validation Data Cleaning

Education

Degrees, certifications, and relevant coursework

Northwestern University

Master of Science, Analytics

2016 - 2017

Completed a Master of Science in Analytics, focusing on applied data science, statistical modeling, and machine learning for business applications.

University of Colorado Boulder

Bachelor of Science, Mathematics & Economics

2011 - 2015

Earned a Bachelor of Science in Mathematics and Economics with a minor in Computer Science, emphasizing quantitative analysis and computational problem solving.