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Matthew Oldach
Verified Expert in Engineering
Software Engineer and Developer
Leduc, AB, Canada
Toptal member since June 10, 2025
Bio
Matthew is a senior consultant with 10+ years’ experience in Python-driven AI/ML systems. He’s led life sciences teams delivering GenAI apps, LLM pipelines, and production model deployments. His expertise spans end-to-end MLOps—from data ingestion and training to CI/CD, monitoring, and cloud orchestration. Matthew uses Python for model development and infrastructure-as-code, integrating GenAI tools to solve complex scientific and business challenges.
Portfolio
Roche
Kubernetes, CI/CD Pipelines, Infrastructure as Code (IaC), Python, OpenAI...
Amaris Consulting
Python, AWS DevOps, Computational Science, Docker, CI/CD Pipelines, Management...
Roche
Java, JavaScript, TypeScript, Postman, GitHub Actions, Software Development...
Experience
- Computational Science - 10 years
- Data Science - 8 years
- Python - 8 years
- Software Development - 8 years
- GitHub - 8 years
- CI/CD Pipelines - 6 years
- AWS DevOps - 6 years
- Software Deployment - 3 years
Preferred Environment
Linux, Docker, AWS Command Line Interface (CLI), LangGraph, GitHub Actions, Visual Studio Code (VS Code), Python 3, OpenAI API, Kubernetes, Terraform
The most amazing...
...thing I've orchestrated was the AWS migration of Python-based bioinformatics workflows at a top-five pharma, cutting $10,000/month in compute costs.
Work Experience
AI/ML DevOps Engineer
2025 - PRESENT
Roche
- Served as a senior MLOps engineer, building and scaling Python-based ML infrastructure for enterprise GenAI and LLM-powered applications.
- Managed Kubernetes clusters on Amazon Elastic Kubernetes Service (Amazon EKS) to ensure high-availability ML inference services, scaling AI-driven features for enterprise applications.
- Executed model deployment strategies to integrate machine learning models into production environments.
- Implemented infrastructure as code (IaC) with Terraform to provision and optimize AWS-based ML/LLM environments, influencing architectural decisions across the stack.
- Integrated monitoring and logging solutions to track model performance and system health.
- Build FastAPI REST endpoints in Python to support real-time inference for genomics pipelines and sequencing analytics.
- Monitored and improved LLM performance and scalability, collaborating with cross-functional teams to deliver robust, user-focused solutions.
Technologies: Kubernetes, CI/CD Pipelines, Infrastructure as Code (IaC), Python, OpenAI, Anthropic, Gemini, Amazon Bedrock AgentCore, AWS DevOps, Pandas, NumPy, FastAPI, Software Development, Linux, Debugging, Scripting, Programming, Data Wrangling, Automation, DevOps, Machine Learning Operations (MLOps), Software Testing, ETL, Version Control, Cloud Computing, AWS Cloud Computing Services, Large Language Models (LLMs), Large Language Model Operations (LLMOps), Natural Language Processing (NLP), AI Chatbots, OpenAI GPT-4 API, APIs, OpenAPI, Agentic AI, Pytest, GitLab CI/CD
Senior Consultant and Team Lead
2020 - PRESENT
Amaris Consulting
- Oversaw a team of five consultants in the life sciences domain, conducted technical reviews, and mentored junior engineers into leadership roles.
- Ensured robust compliance with HR processes, including timely submission of required documentation.
- Developed an Azure-based LLM application with NLP and web scraping, integrating prompt engineering to enhance consultant-client matching for 200+ users.
- Consulted for Genentech on LLMOps and testing frameworks, partnering with ML engineers to deploy RAG pipelines and GPU-enhanced evaluation systems, improving production LLM usability and reliability for genomic sequencing and enterprise tools.
- Defined scalable AI integration strategies for Roche's product lines, leveraging Terraform and AWS to optimize infrastructure, reducing costs by 30% and accelerating experimentation cycles for cross-functional teams.
Technologies: Python, AWS DevOps, Computational Science, Docker, CI/CD Pipelines, Management, Biology, Software Development, Software Deployment, Linux, Debugging, Scripting, Programming, Data Wrangling, Machine Learning Operations (MLOps), Version Control
Senior Software Engineer in Test
2023 - 2024
Roche
- Built test frameworks for Roche's Sequencing-by-Expansion (SBX) platform, which combines DNA synthesis with nanopore-based reading, and transitioned algorithms from CPU to GPU to improve processing efficiency for whole genome and exome sequencing.
- Developed and executed comprehensive test plans in Java and TypeScript, leveraging GitHub Copilot to accelerate development of signal-to-noise validation suites and ensure reliable base amplification and Xpandomer sequencing accuracy.
- Collaborated with quality engineering, development teams, and project managers to troubleshoot defects, communicate testing outcomes, and support on-schedule delivery of a high-quality SBX prototype.
Technologies: Java, JavaScript, TypeScript, Postman, GitHub Actions, Software Development, Linux, Debugging, Scripting, Programming, Data Wrangling, Automation, Machine Learning Operations (MLOps), Software Testing, ETL, Version Control, Cloud Computing, AWS Cloud Computing Services, Large Language Models (LLMs), OpenAI GPT-4 API, APIs, OpenAPI, Agentic AI, GitLab CI/CD
Senior Scientific Data Curator
2021 - 2023
Roche
- Led the migration of Python-based bioinformatics workflows to AWS using Terraform, building scalable IaC pipelines that reduced compute costs by 40% ($10,000/month).
- Managed Python-driven GitHub workflows and team permissions, improving cross-functional DevOps collaboration for shared GenAI infrastructure.
- Deployed cloud infrastructure via GitLab CI/CD with Python automation, integrating pre-commit hooks, linters, and testing frameworks to improve code quality and accelerate developer throughput by 30%.
- Authored and tuned SPARQL queries in conjunction with Python data ingestion scripts for efficient RDF/OWL handling in ontology-driven experimentation.
- Applied Six Sigma principles in Python-based triage automation, cutting defect turnaround times by 25% and hardening ML production systems.
- Partnered with engineering and product teams to iterate Python-based data solutions aligned with user needs, enhancing the delivery speed of curation tools.
Technologies: Python, R, Jenkins, AWS DevOps, AWS Deployment, CI/CD Pipelines, GitLab, GitHub, Data Migration, Biology, Pandas, NumPy, Software Development, Linux, Scikit-learn, Debugging, Scripting, Programming, Data Wrangling, Data Scraping, Automation, DevOps, Machine Learning Operations (MLOps), Software Testing, ETL, Version Control, Cloud Computing, AWS Cloud Computing Services, Natural Language Processing (NLP), AI Art Visualization, Generative Adversarial Networks (GANs), APIs, Pytest, GitLab CI/CD
Bioinformatician
2020 - 2021
University of Calgary
- Built reproducible, Python-driven Snakemake pipelines to automate large-scale comparative genomics, accelerating dataset processing and model-ready feature extraction.
- Containerized Python-based bioinformatics toolchains using Docker and Singularity, ensuring portability and consistency across hybrid compute environments.
- Created Python-based data visualizations of gene expression patterns to identify novel therapeutic targets and support cross-functional research teams in validating hypotheses.
- Worked cross-functionally with domain scientists to refine experimental workflows, integrating Python automation to boost reproducibility and accelerate genomic discovery cycles.
Technologies: R, Snakemake, High-performance Computing (HPC), Workflow, Python, Molecular Biology, Computational Biology, NumPy, Matplotlib, PySpark, Software Development, Linux, Scikit-learn, Debugging, Scripting, Programming, Data Wrangling, Data Scraping, Automation, DevOps, Machine Learning Operations (MLOps), Anaconda, Software Testing, ETL, Version Control, Cloud Computing, AWS Cloud Computing Services, AI Art Visualization, Generative Adversarial Networks (GANs), APIs, GitLab CI/CD
Bioinformatician
2018 - 2019
CeMM Research Center for Molecular Medicine of the Austrian Acadaemy of Science
- Designed and implemented data pipelines in Python and R to process ChIP-seq, RNA-seq, and clustered regularly interspaced short palindromic repeats (CRISPR) screening datasets, enabling efficient analysis of high-throughput genomic data.
- Optimized pipeline performance using parallel processing techniques, reducing analysis runtime from hours to minutes and accelerating the delivery of actionable research insights.
- Collaborated with interdisciplinary teams, including postdoctoral researchers and graduate students, to validate statistical models and ensure robust, reproducible insights for publication and experimental follow-up.
Technologies: R, Data Visualization, Data Analysis, Data Science, Data Cleaning, Data Validation, NumPy, Matplotlib, Software Development, Linux, Scikit-learn, Debugging, Scripting, Programming, Data Wrangling, Data Scraping, Machine Learning Operations (MLOps), Anaconda, ETL, Version Control, Cloud Computing
Bioinformatician
2018 - 2019
Douglas Mental Health University Institute
- Designed and implemented R-based data pipelines for methylation and genotyping studies, efficiently processing high-dimensional genomic datasets to support psychiatric research.
- Optimized pipeline performance by integrating Rcpp parallelism, reducing runtime from 14 hours to 5 minutes and significantly accelerating research delivery timelines.
- Collaborated with interdisciplinary teams to validate statistical models, ensuring robust data insights for downstream analysis and publication readiness.
- Documented pipeline enhancements and shared best practices, boosting team efficiency and improving data reliability.
- Authored detailed documentation and Python-based reproducibility scripts, standardizing best practices and increasing overall pipeline robustness.
Technologies: R, Statistics, Computational Biology, Data Science, Data Visualization, Presentations, NumPy, Matplotlib, Software Development, Linux, Scikit-learn, Debugging, Scripting, Programming, Data Wrangling, Machine Learning Operations (MLOps), Anaconda, ETL, Version Control, Cloud Computing, AWS Cloud Computing Services
Experience
vapoRwave
https://github.com/moldach/vapoRwavevapoRwave is an R package that brings vaporwave-inspired themes to ggplot2, drawing from a genre of electronic music and art known for its nostalgic and satirical takes on consumer culture, glitch art, anime, 3D objects, and cyberpunk aesthetics.
Explore vapoRwave v0.2.0 and experience the fusion of retro visuals and modern data visualization—now fully integrated with the Synthwave85 RStudio IDE for an immersive coding experience.
This release simplifies installation across operating systems and introduces the New Retro theme in your IDE. It also includes a pre-configured Python environment via the reticulate package. Python users can now enjoy a retro-themed workspace while benefiting from R's intuitive syntax and powerful graphics capabilities.
Explore vapoRwave v0.2.0 and experience the fusion of retro visuals and modern data visualization—now fully integrated with the Synthwave85 RStudio IDE for an immersive coding experience.
This release simplifies installation across operating systems and introduces the New Retro theme in your IDE. It also includes a pre-configured Python environment via the reticulate package. Python users can now enjoy a retro-themed workspace while benefiting from R's intuitive syntax and powerful graphics capabilities.
Hinuhinu
https://moldach.github.io/project/hinuhinu/Hinuhinu is an interactive Shiny web app crafted in R to create rich, custom maps of Hawaii. The project was born from inspiration drawn from bivariate mapping examples and spatial visualizations, adapted here to combine relief terrain and geographic data in a user-friendly interface.
• Leverages ggplot2, sf, and elevation data to render multi‑scale maps of the islands, from statewide to city block level, with overlay support for shapefiles and ocean/land distinctions.
• Utilizes rayshader to generate stunning 3D terrain visualizations and “fly‑by” animations, overcoming Shiny hosting limitations via pre-rendered videos.
• Built as a learning vehicle for Shiny, spatial mapping, and release cycles; employs RAGE principles to iterate fast and ship the app early.
• Basemap generation logic exists in a companion Mahalo package, keeping the Shiny app lightweight and modular.
• First-class UI design inspired by award-winning Shiny apps, ensuring ease of use for non-GIS users to export maps as PNGs/PDFs.
• Leverages ggplot2, sf, and elevation data to render multi‑scale maps of the islands, from statewide to city block level, with overlay support for shapefiles and ocean/land distinctions.
• Utilizes rayshader to generate stunning 3D terrain visualizations and “fly‑by” animations, overcoming Shiny hosting limitations via pre-rendered videos.
• Built as a learning vehicle for Shiny, spatial mapping, and release cycles; employs RAGE principles to iterate fast and ship the app early.
• Basemap generation logic exists in a companion Mahalo package, keeping the Shiny app lightweight and modular.
• First-class UI design inspired by award-winning Shiny apps, ensuring ease of use for non-GIS users to export maps as PNGs/PDFs.
Shiny-filteRs
Shiny-filteRs is a mobile-first Shiny app inspired by Instagram, built using shinyMobile, shinysense, and over a dozen R and Python libraries. It lets users apply artistic, mathematically derived filters (e.g., Voronoi, GlitchArt) to photos. The app showcases cross-language development, leveraging Python for image processing and R for UI. Though some filters weren’t fully realized due to platform constraints, the project demonstrates agile, user-centered design and creative technical integration. It was submitted to the 2021 RStudio Shiny Contest.
Education
2013 - 2015
Master's Degree in Biological Sciences
University of Calgary - Calgary, AB, Canada
2007 - 2011
Bachelor's Degree in Marine Biology
Dalhousie University - Halifax, NS, Canada
Skills
Libraries/APIs
Pandas, NumPy, OpenAPI, Matplotlib, PySpark, Scikit-learn, OpenAI API
Tools
AWS Command Line Interface (CLI), GitLab CI/CD, AWS Deployment, GitLab, GitHub, Snakemake, Pytest, Postman, Jenkins, Terraform
Languages
Python, R, Java, JavaScript, TypeScript, Python 3
Paradigms
High-performance Computing (HPC), Software Testing, Automation, DevOps, ETL, Management
Platforms
RStudio, Linux, Docker, Anaconda, AWS Cloud Computing Services, Kubernetes, Visual Studio Code (VS Code)
Industry Expertise
Bioinformatics
Storage
Data Validation
Frameworks
LangGraph, RStudio Shiny, Framework7
Other
GitHub Actions, Biology, Computational Science, R Programming, AWS DevOps, CI/CD Pipelines, Software Development, Software Deployment, Workflow, Molecular Biology, Computational Biology, Data Science, Data Analysis, Data Cleaning, Debugging, Scripting, Programming, Data Wrangling, Version Control, AI Chatbots, Ecology, Data Migration, Data Visualization, Presentations, Data Scraping, APIs, Cloud Computing, Large Language Models (LLMs), Large Language Model Operations (LLMOps), AI Art Visualization, Generative Adversarial Networks (GANs), OpenAI GPT-4 API, OpenAI, Agentic AI, Scuba Diving, Statistics, Infrastructure as Code (IaC), Anthropic, Gemini, Amazon Bedrock AgentCore, FastAPI, Machine Learning Operations (MLOps), Natural Language Processing (NLP)
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