Job title: Senior Machine Learning Engineer
Reporting to: Head of Data Engineering
Location: Cape Town (Hybrid)
ALL STAFF APPOINTMENTS WILL BE MADE WITH DUE CONSIDERATION OF THE COMPANY’S EE TARGETS
WHAT WE DO
Lula is an innovative and human-focused FinTech company on a mission to help small businesses optimise their cash flow. Our purpose is to help SMEs manage their businesses better, faster, and more simply, so they can spend more time doing what they love.
If you’re looking for a new place to call ‘home’ that believes in the potential of the broader SME landscape in South Africa and a place where you’ll work with awesome people - then Lula’s the place for you!
We’re making business banking fast, human, Lula!
OUR VALUES
Collaborative - we’re a clan and work together as a team, always towards a common goal
Committed - we’re accountable and follow through no matter the challenge
Curious - we look for better ways to do things and make a positive difference
Connected - we stay close to, learn from and look to understand each other and our customers
Compassionate - we go out of our way to care about our colleagues, our customers and our community
OVERALL PURPOSE
As a Machine Learning Engineer, you will design, build, and deploy machine learning models to solve complex problems and enhance business processes. You will work with large datasets to preprocess, analyse, and extract meaningful insights, while collaborating with data scientists, software engineers, and other stakeholders to integrate machine learning solutions into production systems. You’ll be responsible for selecting the appropriate algorithms, fine-tuning model performance, ensuring scalability, and maintaining model reliability after deployment.
You will also apply industry best practices in model development and data handling.
Responsibilities will Include, but are not limited to:
- Consult with data scientists on training machine learning models
- Support improvements and additions to the ML infrastructure, including hands-on involvement with data engineering and DevOps engineering tasks
- Design systems to meet throughput and latency requirements
- Implement NFRs (Non-Functional Requirements) to ensure a high degree of system reliability
- Design and implement Feature Store
THE COMPETENCIES WE’RE AFTER
- Clear and concise communication and documentation skills
- Process-orientated with experience in Agile
- Team-player with a desire to collaborate
- Critical thinking skills
- Focused on high quality output
- Self-starter
THE SKILLS AND EXPERIENCE WE’RE LOOKING FOR
- Bachelor's degree in Computer Science, IT, or related field
- 6+ years experience as a Machine Learning Engineer or in a similar role
- 4+ years experience with productionising ML systems is a must
- 4+ years experience training machine learning models is highly desirable
- Advanced knowledge of Python and familiarity with SQL
- Good working knowledge of Terraform for Infrastructure as Code (IaC)
- A solid understanding and hands-on experience with real-time and event-driven systems such as Kafka, Kafkaconnect, Pub/Sub.
- Solid experience with Kubernetes, docker, deployment types (canary, blue-green etc.)
- Experience with setting up CI/CD systems using tools such as CircleCI, drone, Github actions, ArgoCD
- Working experience with Big Data technologies such as Spark, Dataflow, and Flink
- Experience with system design - keeping performance and efficiency in mind, whilst aware of trade-offs
- Experience applying software engineering rigor to ML, including CI/CD/CT, unit-testing, automation etc.
- Hands-on experience with some MLOps tools such as KubeFlow, DVC, MLFlow.
- Experience with cloud providers, such as GCP, AWS, or Azure
- Prior experience in, or a strong interest in, the FinTech industry
Please note that all appointments are subject to our background checking process, which may include Credit, Criminal and any other job inherent checks.