Job Description
KnowBe4 is the global leader in Human Risk Management, trusted by over 70,000 organizations worldwide to secure their employees and AI agents for over 15 years. We’re pioneering a new era of security. AI-powered since 2016. And market-leading since day one.
Our HRM+ combines continuous risk intelligence, advanced technical defenses, and personalized training to help organizations build strong security cultures. We help organizations understand, measure, and reduce human risk across their entire workforce, defending against, deepfakes, and emerging AI-powered threats.
We believe that protecting organizations from cyberthreats and creating a positive environmental impact go hand in hand. True resilience is collective, it requires us to protect our people, our data, and our planet.
Please submit your resume in English.
To learn more about our team and office culture in Cape Town, South Africa visit the following links.
Careers Page: https://www.knowbe4.com/careers/locations/cape-town
Glassdoor: https://www.glassdoor.com/Location/KnowBe4-Cape-Town-Location-EI_IE969384.0,7_IL.8,17_IC2653748.htm
LinkedIn: https://www.linkedin.com/company/knowbe4/life/southafrica/
We are looking for a Machine Learning Engineer to help scale the industrialization of our ML lifecycle. This is a Builder’s Role - you will be responsible for the high-scale architecture that allows our models to survive production. You’ll be a key contributor to our MLOps ecosystem, moving beyond experimentation to build high-throughput, distributed systems that serve as the backbone of our intelligence products.
Machine Learning Engineers help us extract value from our data. They are involved in all the processes from data collection, cleaning, and preprocessing, to training models and deploying them to production. This position will assess, analyze, and organize data, execute tests, and optimize the learning process to develop high-performance machine learning models.
Responsibilities:
- Develops software using the KnowBe4 Software Development Lifecycle and Agile Methodologies
- Designs, develops, and researches Machine Learning systems
- Transforms data science prototypes by applying appropriate Machine Learning algorithms and tools
- Performs statistical analysis and using results to improve models
- Inference Engineering: Drive the deployment and optimization of both standard predictive models and LLM architectures, balancing trade-offs between low latency, high throughput, and cost-efficiency
- Platform Hardening: Transition research prototypes into resilient, production-ready microservices that can handle massive traffic
- Lifecycle Orchestration: Execute automated pipelines for data and model versioning, validation, and retraining
- Observability: Implement advanced monitoring for model drift, data integrity, and system health to ensure production reliability
- Collaborative Standards: Uphold clean code practices, thorough documentation, and participate in rigorous code reviews across the ML and Engineering teams
Requirements:
- BS or equivalent plus 3 years experience
- MS/Ph.D. or equivalent plus no experience
- Training in secure coding practices (preferred)
- AI/ML and Core: Python (production-grade), PyTorch
- Data and Features: Apache Spark for distributed processing; experience with Feature Stores or automated feature engineering is a plus
- Infrastructure: AWS (SageMaker, Lambda), Docker, and Terraform/IaC for environment reproducibility
- Specialized Tooling: Experience with custom inference optimization (Python-based); orchestration via lean, custom AWS and Python-based solutions using Lambda and MLflow
- Additional: C# and JavaScript (beneficial)
- Familiarity with secure coding practices
The Reality Check:
While the title says pure ML, the day-to-day is data heavily and is also focused on the AI and ML Platform Engineering around our services. Expect a roughly 90⁄10 split - the vast majority of your impact will come from hardening data pipelines, refining CI/CD for ML, and building world-class observability, with the remaining portion dedicated to model building, implementation and tuning.
Our Fantastic Benefits
We offer company-wide bonuses based on monthly sales targets, employee referral bonuses, adoption assistance, tuition reimbursement, certification reimbursement, and certification completion bonuses - all in a modern, high-tech, and fun work environment. For more details about our benefits in each office location, please visit www.knowbe4.com/careers/benefits.
Note: An applicant assessment and background check may be part of your hiring procedure.
Individuals seeking employment at KnowBe4 are considered without prejudice to race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, sexual orientation or any other characteristic protected under applicable federal, state, or local law. If you require reasonable accommodation in completing this application, interviewing, completing any pre-employment testing, or otherwise participating in the employee selection process, please visit www.knowbe4.com/careers/request-accommodation.
No recruitment agencies, please.
