Dr. Chris Fourie#

Research MLOps Engineer | Medical Doctor | Community Builder | High Risk Responsible AI Practitioner#

Medical doctor turned Research MLOps engineer trying to use the powers of AI for social good. Currently working full-time as a Lead Research MLOps Engineer at DVT Software, a South African software consultancy operating globally with 600+ IT professionals, with focus on AI infrastructure for major financial institutions.

💡 Industry Experience Highlights

  • 2025-ongoing: Lead MLOps Engineer at ABSA Bank (ZA) (via DVT Software) on MLOps project for commercial international banking credit risk analysis for large corporate clients
  • 2023-2025: Data/MLOps Engineer at Western Cape Provincial Health Data Centre
    • built digital infrastructure for privacy-preserving federated health data analysis
    • Co-Principal Investigator: 2-year federated analysis with Brazilian research group CIDACS investigating TB and syphilis in pregnancy (Gates Foundation funded)
  • 2020-2023: MLOps Engineer at LifeQ - health/biometric data analysis from continuous monitoring devices, COVID detection using wearables

⚙️ Technical Expertise

My experience primarily spans MLOps engineering for research in high risk AI enabling AI experimentation and service delivery on sensitive health and financial data

  • MLOps Engineering: Software engineering (cloud, backend, and DevOps), data engineering and data science
  • Infrastructure: AWS/Azure, Docker, Kubernetes, Terraform, Databricks, CI/CD pipeline development, end-to-end ML pipelines, model serving
  • Privacy-Preserving AI: Large-scale federated analysis of observational health data, synthetic data generation, federated learning systems
  • Research Domains: Healthcare data analytics, financial AI, multi-modal ML for health
  • Specialised Tools: Container-based microservices, ETL pipelines, secure data environments for research

🎓 Education & Research Background

🌍 Community Leadership & Impact

  • Currently founding: C3Data.Africa, the "African Data Commons Cooperative Collective", building communities for federated African data cooperatives.
  • Currently founding: MLOps.Africa, a grassroots community of practice for African MLOps practitioners
  • Co-founder: SisonkeBiotik (2020) - grassroots participatory research community making AI/ML for health research in Africa more accessible
  • Co-founder: AfriMedQA project - novel benchmark dataset with rigorous evaluation of 20+ LLMs for African healthcare data, spanning 32 clinical specialties, contributed by 1k+ African clinicians across 15 countries
  • Technical Advisor / Steering Committee: Data Science Without Borders project - developing capacity for federated health data analyses across institutions in Cameroon, Ethiopia and Senegal

💡 Motivation & Vision

I'm motivated by my experience growing up in South Africa, witnessing the devastating effects of perpetuated inequity. During my medical training, I saw first-hand the challenges this creates - the severe impact that resource scarcity and the legacy of colonialism can have on the health and wellbeing of individuals and their communities.

My long-term career interests intersect at collaboratively developing industry solutions and forwarding academic efforts to address inequity, with close consideration for the diverse and complex nature of our societal systems.

Resume#

     

Industry experience#

Current commitments#

Full-time#

From 2025 - Lead MLOps Engineer at DVT Software

  • Lead MLOps Engineer on project for ABSA Bank (ZA), to improve internal models using AI and forward development of internal AI infrastructure

Part-time#

From 2024 - Technical advisor on steering committee for Data Science Without Borders project

  • Providing strategic direction and feedback on technical design of systems for federated health data analyses and federated machine learning

Previous experience#

Full-time#

2023 to 2025 - Data / MLOps engineer for the South African Western Cape Provincial Health Data Centre

  • Built digital infrastructure for large scale privacy preserving federated analysis of observational health data
  • Successfully delivered as a co-principal investigator on a 2 year federated analysis with Brazilian national research group CIDACS investigating TB and syphilis in pregnancy funded by the Bill and Melinda Gates Foundation
  • Project lead to establish secure data environments / trusted research environments for research data accessibility, developing tooling for de-identified and synthetic data
  • Project lead for CI/CD pipeline development and Python dependency management in Databricks
  • Development and maintenance of data pipelines for data ingestion and processing from both provincial public health facilities and national public health data repositories

2020 to 2023 - MLOps Engineer and Health Data Scientist for LifeQ (US)

  • Working on projects related to analysis of health / biometric data from continuous and remote monitoring devices
  • Generally, machine learning and data pipelines, backend, DevOps and cloud infrastructure for AI / machine learning
  • Lead on project to investigate using biometric data from wearables for COVID detection, optimised existing approach by decreasing resource requirements while increasing accuracy with multi-modal approach
  • Lead on project for rapid model benchmarking pipeline
  • Worked on project to standardise data science projects as serverless AWS Chalice apps with focus on parallelisation of data pipelines and containerisation

2020 - MLOps Engineer internship at DataProphet (ZA)

  • Projects on ETL and cloud orchestration for ingestion of factory sensor data to ML and data pipelines.

Part-time#

2024 - Technical consultant for FruitPunch AI (Netherlands)

  • Developing experimentation and data pipelines for LLM based inference on genomics data using MPEG-G compression

2024 - Technical strategy consultant for MotherDAO Labs (USA)

  • Developing AI strategy and conducting feasibility analyses for delivering high quality community feedback data for AI alignment customers with a focus on preference and reward modelling

2023 - Independent technical consultant for RetroRabbit (ZA)

  • Conducting technical interviews for intermediate and senior software engineers

2022 - Technical strategy consultant for Cebisa Health (ZA)

  • Strategy consulting for feasibility and implementation of electronic health record platform for schools in Africa

2020 - Technical consultant for Mamba Insights (UK)

  • MLOps software solution implementation for video segmentation and analysis in industrial settings

Platforms / tools / frameworks#

  • Languages: Python, C, Java, TypeScript
  • Cloud
    • AWS: Boto3, Chalice, Batch, SQS, SageMaker, Lambda
    • Terraform
  • DevOps: Jenkins, Airflow, Azure DevOps
  • Backend: SQL (Postgres, SQL Server), noSQL (DynamoDB)
  • Data engineering: Databricks, PySpark, Pandas

  • Data science / ML:

    • Neural Networks: PyTorch, TensorFlow
    • Scientific computing: SciKit learn, NumPy
    • Experimentation: MLFlow, Weights & Biases
    • Data visualisation: Seaborn, Matplotlib

    • Computer vision: OpenCV

    • Reinforcement learning: OpenAI Gym, Stable Baselines

    • Docker, Git, Linux

More info on MLOps here

Academic experience#

Selected publications#

  • 2025 - "AfriMed-QA: A Pan-African, Multi-Specialty, Medical Question-Answering Benchmark Dataset" - ACL - Best Paper Award for Social Impact [paper][socials]
  • 2024 - "AfriBiobank: Empowering Africa's Medical Imaging Research and Practice Through Data Sharing and Governance (MICCAI) [paper]
  • 2023 - "A Framework for Grassroots Research Collaboration in Machine Learning and Global Health", ICLR 2023 (ML for Global Health) [paper]
  • 2018 - Chapter Co-Author on "Trauma and Injury" for Essentials of Global Health textbook (British Medical Journal Book Awards, 1st place in Public Health division, published by Elsevier, edited by Parveen Kumar) [textbook]

Education#

Communities and academic affiliations#

From 2020 - SisonkeBiotik (co-founder) [community site], [YouTube], [LinkedIn], [Twitter]

  • Led efforts to found community, developed initial structures, policies and practices
  • Lead for initial projects, events and fundraising efforts
  • Advising leadership team
  • Developing and maintaining strategic relationships

2019-2023 - RAIL Lab (member) - [blog], [members]

2023 - Deep Learning Indaba (community organiser) - [community site]

2021-2023 - IndabaX South Africa (community organiser) - [community site]

2019 - Computational Neuroscience Imbizo (alumni) - [summer school]

ComSci MSc - Research report#

[full report]

Impact of Noise on Learned Value Functions at Depth in CoAgent Networks for Neural Network Credit Assignment

CoAgent networks (CoANs), networks of reinforcement learning agents, have been shown to be a biologically plausible alternative to backpropagation for solving the neural network structural credit assignment problem [Gupta et al. 2021]. This is accomplished where many agents, each as a neuron in a stochastic neural network, use only their local policy gradient and a global reward. Noise is an important consideration in the learning dynamics of any stochastic neural network [Schoenholz et al. 2017]. We investigate the impact of noise on learnt value functions for baselines and Actor-Critic methods in CoANs at depth. We demonstrate that with additional layers, CoANs using REINFORCE, REINFORCE with a baseline or Actor-Critic methods perform significantly worse. However unbiased variance reduction methods are effective at alleviating this to a moderate extent. For CoANs of increasing depth and width using Actor-Critic methods we show that learned value functions are more sensitive to noise. We show as well that large bootstrapping bias impacts Actor-Critic CoAN methods significantly.

ComSci MSc - Projects#

Machine Learning#
Reinforcement Learning#
Computer Vision#
High Performance Computing#

Algorithm Analysis#

  • Recursive Algorithms - Find max sub-array (Java) - [repository]
  • Search trees - Binary, Red Black and Order statistic (Java) - [repository]

Robotics#

Conferences and talks#

  • 2024 - Invited speaker for Africa Health Exhibition ("3IR b4 4IR: Data Accessibility to Enable African Data Science, ML and AI for Health" [slides])
  • 2023 - Invited speaker AI for health @ ICLR / IndabaX Rwanda ("AI 4 Health in Production" [slides])
  • 2023 - Deep Learning Indaba (organising committee)
  • 2023 - DS4Health Workshop @ Deep Learning Indaba (lead organiser)
  • 2023 - Deep Learning IndabaX South Africa (organising committee)
  • 2023 - Invited speaker AI for health @ IndabaX Zimbabwe
  • 2022 - African Machine Learning 4 Health Workshop @ Deep Learning Indaba (lead organiser)
  • 2022 - Deep Learning IndabaX South Africa (organising committee)
  • 2021 - Deep Learning IndabaX South Africa (organising committee)
  • 2020 - African Institute for Mathematical Sciences (AIMS) African Machine Learning Masters (AMMI) Rwanda, Reinforcement Learning Course (tutor)
  • 2019 - Deep Learning Indaba, Kenyatta University, Nairobi Kenya (presented poster on pan-African ML for health collaboration)
  • 2019 - IBRO-Simons Computational Neuroscience Imbizo / Summer School (participant fully funded)
  • 2014 - South African Medical Association (SAMA) annual conference (student delegation leader)
  • 2013 - IFMSA General Assembly, Tunisia (South African delegation leader)

Career direction and opportunity seeking#

There are a variety of career paths I anticipate would bring me joy and prosperity while affording me an opportunity to make a positive impact.

I am interested in being contacted to explore full-time / part-time opportunities in industry / research that are related to any combination of the following:

  • MLOps engineering (Software, backend, DevOps, data and ML engineering)
    • Solution design, implementation and maintenance
    • AI / data pipelines, AI digital infrastructure
    • Responsible AI
  • AI for health
    • Privacy preserving AI for health
    • Multi-modal ML for health
    • AI for adaptive treatment regimes
  • Public and global health
    • AI for data driven health policy development

  • Collective intelligence

    • AI for resource governance
    • Multi-agent modelling
    • AI for multi-agent credit assignment
    • Emergent communication
    • Technical consulting
    • Software and digital
    • Strategy
    • Feasibility
    • Solution design / architecting and implementation
    • Democratic business / co-operatives

References#

Prof. Benjamin Rosman
RAIL Lab Director
University of the Witwatersrand
Email: Benjamin.Rosman1@wits.ac.za
Website: https://www.benjaminrosman.com
Citations Time's 100 Most Influential in AI 2025

Prof. Andrew Boulle
Technical Director at the
Western Cape Government Provincial Health Data Centre
Public Health Specialist
andrew.boulle@westerncape.gov.za
Citations

George Cooper
Team Lead at LifeQ
MLOps Engineer and Systems Biologist
+27829222334

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