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 heavy 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.

About us:

We believe the next generation of financial services will be powered by stablecoins.

Founded in 2021, our mission at BVNK is to accelerate global money movement.

We’re building stablecoin-native infrastructure so businesses can move value instantly across borders and networks. With global licenses and T1 bank partnerships, we facilitate billions in transactions for enterprise clients like Worldpay, Deel, LianLian Global, and Rapyd.

Our technology is transforming how businesses operate globally by eliminating payment delays, reducing costs, and unlocking trapped capital. 

We’re a diverse team spread across EMEA, North America, and APAC, with a shared belief that stablecoins are the new infrastructure layer for financial services, and that BVNK is at the forefront of this shift.

In 2025, we secured strategic investment from Visa, following our $50 million Series B with Haun Ventures, Coinbase Ventures, Scribble Ventures, DRW Venture Capital, Avenir, and Tiger Global. With the backing of these leading investors, we’re accelerating our growth – and we're looking for smart, ambitious people to help us build the future of financial services.

We're incredibly honored to have made Newsweek's list of The Top 100 Global Most Loved Workplaces three years running (most recently in 2025) and to have been recognised by LinkedIn as one of the Top 20 Startups in the UK in 2024

About this role in the team:

We are looking for a QA Engineer who views AI as their primary leverage. At BVNK, we aren't just looking for someone to maintain scripts; we want an engineer who views manual, repetitive testing as a problem to be solved with intelligent agents.

You will join a team of Quality Assurance experts responsible for the end-to-end integrity of our Fiat and Crypto products. Your mission is to evolve our testing from "automated" to "autonomous." You will build intelligent testing systems that predict failures, self-heal scripts, and utilize LLMs to bridge the gap between complex financial requirements and bulletproof code.

Key Areas of Responsibilities:

• AI-First Framework Evolution: Architect and maintain automation frameworks that prioritize AI-powered solutions for test generation, execution, and self-healing.
• Autonomous Quality Gates: Implement AI-driven gates in our CI/CD pipeline to predict regression risks before code is even merged.
• Synthetic Data Strategy: Leverage Generative AI to create complex, high-integrity test data sets for diverse global payment scenarios.
• Intelligent Observability: Use AI to analyze logs and system behavior, providing insights that traditional testing tools miss.
• Mentorship & AI Evangelism: Act as the subject matter expert on emerging AI tools (Claude Code, LangChain) to upskill the broader QA team.

What we need from you:

• AI-Native Mindset: You are an early adopter of LLMs and agentic workflows. You don't just use AI to write snippets; you use it to architect solutions.
• Technical Core: Expert-level proficiency in Python (our primary language) and the ability to navigate Java environments.
• Modern Tooling: Hands-on experience with PyTest, Playwright, and K6.
• Engineering for AI: Demonstrated experience implementing AI solutions for test case generation and automated bug triaging.
• Infrastructure Fluency: Familiarity with CI/CD concepts and desire to understand the integration of AI-driven testing into the deployment lifecycle.
• Precision & Speed: Exceptional attention to detail with the ability to move fast in a rapidly evolving FinTech environment.
• Bonus: LLM Integration: Experience building custom GPTs or using LangChain/LangSmith/LangGraf to evaluate LLM-based product features.
• Bonus: FinTech & Crypto: Previous experience in payments, stablecoins, or blockchain technology.
• Bonus: Agentic Testing: Experience experimenting with autonomous agents for exploratory testing.

What you can expect from us:

• Fair and competitive salary at every stage of your growth
• Meaningful ownership in the business through our employee option scheme
• Flexible working hours, with hybrid working at its heart
• A culture built on passionate growth-minded people
• A flexible approach to holiday
• Opportunities to travel to our offices around the world
• An open and creative environment where you can help us define the future of BVNK, its culture, and its opportunity sets

At BVNK, we are focused on building a diverse and inclusive team. While you may not meet all of our requirements, we’d encourage you to apply if you meet the majority of our expectations. You may be a great fit for this role or another role in our team. 

The Ideal Candidate

As part of our transformation journey toward quality automation, we are strengthening our Quality Engineering capabilities. We are looking for a pragmatic Quality Engineer who can take ownership of manual integration testing across multiple teams while also designing and evolving automated test coverage.

This role suits someone comfortable working hands-on across systems today, while actively driving automation maturity over time.

The Role

The Senior Quality Engineer: Automation & Integration Testing is responsible for ensuring high product quality across multiple teams, with a strong initial focus on manual integration testing between three development teams, alongside building and maintaining automated tests.

The role plays a critical part in validating cross-service workflows, identifying integration risks early, and progressively strengthening automation to support continuous integration and delivery. The engineer collaborates closely with development and product teams to embed quality throughout the software development lifecycle.

Responsibilities

• Own and execute manual integration testing across three development teams, validating cross service workflows, data flows, and end to end customer journeys.
• Design and execute risk-based test strategies, using manual and exploratory testing where automation is not yet feasible or effective.
• Define, build, and maintain automated integration and end to end tests, with a clear focus on gradually reducing manual effort through sustainable automation.
• Collaborate closely with developers to validate integration points, APIs, contracts, and system behaviour across environments.
• Build and maintain test infrastructure and utilities (test data, mocks/stubs, environment configuration) to support both manual and automated testing.
• Integrate automated tests into GitLab CI/CD pipelines, ensuring fast feedback, clear reporting, and reliable quality gates.
• Triage integration issues, automation failures, and product defects, providing clear diagnostics, root cause analysis, and high-quality defect reports.
• Continuously improve test coverage, automation stability, execution time, and maintainability as systems and team maturity evolve.

Skills and Experience

Successful candidates for this role will generally possess the following qualifications and skills:

• 6+ years of experience in software quality engineering, including hands-on manual testing, integration testing, and automated regression execution.
• Strong experience designing and executing manual integration and exploratory tests across distributed systems.
• 3+ years of Java experience building and maintaining automated tests.
• Hands‑on experience with Karate for API and microservice testing, plus mobile automation for iOS/Android (e.g., Appium) and web automation (e.g. Playwright, Selenium).
• Experience with modern test automation frameworks and tools such as TestNG, JUnit5, Cucumber/Gherkin, and build systems like Maven.
• Strong CI/CD experience running automation in pipelines (GitLab pipelines/runners).
• Daily working knowledge of Git based repositories and modern SDLC practices.
• Experience working in Agile/Scrum teams.
• Experience using AI assisted tools (e.g., GitLab Duo, Copilot, LLM based assistants) with strong validation of outputs.
• Strong 10101 analytical and problem-solving skills.

Personality Attributes

• Positive, professional attitude with excellent written and verbal English communication skills.
• Collaborative and supportive; effective working with cross functional teams.
• Self-starter, with strong ownership in an autonomous environment.
• High attention to detail and consistent adherence to defined processes.
• Comfortable working to deadlines in a fast-paced environment, both independently and as part of a team.