Chris Poptic

Agent Ops Engineer

Eliza

Jun 2026 - Current (3 months)

Building the platform to help our Forward Deployed Engineers build, deploy, and iterate faster and easier.

AI Engineer / LLM Engineer

Boston Consulting Group (BCG)

Aug 2025 - Apr 2026 (9 months)

AI & LLM engineer @ BCG through Eliassen Group LLC. - Built a search query optimizer using Bayesian optimization to optimize query and field boosts in Elasticsearch query to maximize relevancy metrics (precision, recall, MRR, etc) - Built web app dashboard with FastAPI/Streamlit to enable self-service relevance metrics calculations. - helped build an AI agentic workflow pipeline to rapidly build and deploy AI agents. - helped build tools that connect via MCP to enable searching, fetching, etc of documents from Elasticsearch indexes.

AI/MLOps Engineer

Take-Two Interactive

Sep 2024 - Jun 2025 (10 months)

MLOps engineer through Eliassen Group LLC. * Led small team that built and deployed MLOps platform using AWS and Databricks Asset Bundles for managing ML model versions, ensuring reproducibility, monitoring for data drift and model drift, providing a data lineage of models for auditing, and enabling one-click deployment of ML models built by data scientists. * Fully owned the end-to-end training, testing, and deployment of a profanity detection model using ML and LLMs (specifically Llama 3.1) to automate the process of identifying profane lyrics from in-game songs, which resulted in a significant reduction in the tedious, time-consuming manual lyrics review process, resulting in ~$k reduction in overall cost and a 83% decrease in time to co

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Sr Machine Learning Engineer

GoldBelly

Sep 2023 - May 2024 (9 months)

* Built, trained, deployed, and scaled a LLM-based retrieval-augmented generation (RAG) chatbot to enable customers to more effectively search products for specific intention-based recommendations, using ChatGPT 4, LangChain, LlamaIndex, Python, FastAPI, AWS, and Chroma vector database. Improved RAG performance and reduced cost of chatbot inference by $120,000/yr by incorporating re-ranking, prompt engineering, query expansion, and a 2-stage retriever with Elasticsearch. Improved model inference and serving by 3x using vLLM. Chatbot deployment resulted in 11% increase in ATC and 2% increase in CVR. * Increased search-ranker service NDCG by 7% and MAP by 9% through incorporating sparse and dense multimodal vector embeddings of product featur

Staff Data Scientist

Twist Bioscience

Jan 2023 - Aug 2023 (8 months)

* Built model to predict risk of gene misassembly using Python, Pandas, XGboost, Snowflake, AWS. * Built data pipeline for NGS data to enable repeatable, reproducible model training, implemented MLOps standards, and built a dashboard with MLFlow and Evidently on Databricks to monitor data drift and model drift in productionized models. * Tracked and versioned trained models using MLFlow. * Applied image analysis using PyTorch and OpenCV to track the cultivation of E. coli colony growth over time while to better predict NGS outcomes.

Sr Machine Learning Engineer

Genentech

Apr 2022 - Oct 2022 (7 months)

* Oncology Biomarker Discovery (OBD) group. * Built robust, modular, testable ML pipelines for computer vision tasks (image classification, segmentation, object detection) in digital pathology from large Whole Slide Images and NGS data to classify cancer subtypes using PyTorch, PyTorch Lightning, OpenCV. * Set up ML pipeline to automate the process of ingesting, validating, and preprocessing new data, triggering new model training jobs conditional on model drift using NVIDIA MONAI and RAPIDS, and deploying models to production using AWS services (SageMaker, ECR, ECS). * Automated the CI/CD of models with AWS CodePipeline to orchestrate builds and MLFlow to version models.

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Sr Data Scientist

nference

Dec 2020 - Mar 2022 (1 year 4 months)

* Built analytical and predictive models for cohort analysis of patient outcomes of a clinical trial for a large pharmaceutical client using Mayo Clinic patient database. * Trained a BERT model on EHR clinical notes to perform patient phenotyping and predict patient outcomes (hospital readmissions, mortality risk, disease progression) based on the analysis of longitudinal clinical notes data. * Calculated survival analysis for clinical events using Kaplan Meier curves. * Leveraged a Ray cluster to configure and run parallel and distributed ML model training jobs across hundreds of GPUs.

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Senior ML/AI Engineer

Pacific Dental Services (via Ntersol)

Jul 2019 - Nov 2020 (1 year 5 months)

* Led overall data science strategic direction including identifying, evaluating, and executing data-driven projects with a focus on leveraging machine learning. * Led a team to build several computer vision models to automatically detect dental pathologies from patient x-ray images using TensorFlow, PyTorch, CV2, and Facebook’s Detectron2 library, trained on dataset of ~25,000 annotated x-ray images in DICOM files. * Built an image classification model (AUC of 0.92) to detect quality of an x-ray image and predict likelihood of whether or not image would be denied in a dental insurance claim. * Tuned neural network using learning rate schedulers, various SGD optimizers, and regularization techniques including early-stopping, dropout, and im

Data Scientist, Machine Learning Engineer

Olive

Aug 2018 - Jul 2019 (1 year)

* Developed several computer vision and NLP models to automate repetitive healthcare administrative workflows using Python, PyTorch, PyAutoGUI, and Docker. * Trained model using XGBoost to predict customer conversion probability from a large unstructured sales dataset, from which named entities were extracted using BERT model. * Built time series forecasting models (ARIMA, Holt-Winters, XGBoost, LSTM, Prophet, & Temporal Fusion Transformer) on multi-dimensional time series data to forecast future sales.

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Data Scientist, NLP

Illumination Works

Jun 2017 - Jul 2018 (1 year 2 months)

* Used Python and NLP techniques including NLTK, Gensim, SpaCy, TF-IDF, bag of words, and Elmo/GloVe word embeddings to process radiology dictation text and build a medical diagnosis model and recommendation engine that automated the extraction of critical radiological measurements and clinical findings.

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Data Scientist

Data Science Solutions, LLC

Jan 2016 - Apr 2019 (3 years 4 months)

Consulting with startups and other clients build and deploy predictive models into production. Built a classifier model using an attention-based neural network TabNet to predict severity of prostate cancer based on clinical blood-based biomarker data that has 27% higher precision than standard prostate specific antigen (PSA) test. Developed time-series model to predict vehicle malfunctions with streaming OBD-II telemetry data using Kafka, PostgreSQL, Pandas, LightGBM, ARIMA, and an LSTM. Built model to predict probability of pulmonary fibrosis using computer vision techniques including EfficientNet on PyTorch. Developed a tool for a financial client to scrape public text at scale from various alternative data web sources and apply sentiment

Data Scientist

M&S Consulting

Jan 2016 - Dec 2017 (2 years)

Contract for US Army Logistics Branch to build a logistics, supply chain, and inventory tracking and management tool using Apache Spark.

BI Developer, Data Scientist

Tata Consultancy Services

Jun 2013 - Jan 2016 (2 years 8 months)

* Developed business intelligence applications, reports, and dashboards using MicroStrategy, SAP HANA, PowerBI, and Tableau. * Developed regression models using Python and scikit-learn to forecast and predict flight delays based on historical weather data, flight delays, and weather forecasts for medium-size commercial airline client. * Obtained MicroStrategy Certified Developer (MCD) certification.

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Biomedical Engineering co-op in medical device design and risk management

Ethicon Endo-Surgery, Johnson & Johnson

Jun 2006 - Mar 2007 (10 months)

• Reviewed and analyzed technical manufacturing requirements, functional specifications, product design history, and end-user guides for safe and effective use of minimally-invasive surgical instruments • Wrote, edited, and updated technical requirements, functional specifications, product design history, installation guides, training materials, and end-user guides for proper use of minimally-invasive surgical instruments • Assisted in development of a risk management plan for quality control of a new medical device using failure mode and effects analysis, fault tree analysis, and list of material analysis through the Six Sigma process • Ensured that device met risk management requirements per ISO 13485 and ISO 14971 standards • Assisted in

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