The Role
We're looking for a
Machine Learning Engineer
who thrives at the intersection of data science and production systems. You'll design and deploy scalable ML pipelines, optimize model performance, and automate end-to-end workflows ensuring seamless integration between models, data, and business applications.
Snapshot
Location
: Cape Town, Johannesburg, Remote
Employment
Type
: Full-time, Contract
Key Responsibilities
Build and maintain
production-grade ML pipelines
for deployment.
Design
automated workflows
for model retraining, monitoring, and version control.
Optimize
inference speed, scalability, and cost-efficiency
across cloud environments.
Collaborate with
data engineers and data scientists
for seamless model integration.
Work with
containerized ML infrastructure
(Docker, Kubernetes, MLflow).
Monitor
model drift, data quality, and performance metrics
in production.
Maintain high standards of reliability, documentation, and reproducibility.
Skills & Experience
5 - 8+ years
of experience in Machine Learning or AI engineering.
Proficient in
Python
and ML frameworks:
TensorFlow, PyTorch, scikit-learn
.
Hands-on experience deploying models using
Docker, Kubernetes, MLflow
.
Strong understanding of
MLOps principles
and
CI/CD pipelines for ML
.
Familiar with
AWS SageMaker, Azure ML
, or
GCP Vertex AI
.
Nice to Have
Experience with
distributed training
and
GPU optimization
.
Knowledge of orchestration tools:
Airflow, Kubeflow, or Prefect
.
Familiarity with
real-time data streaming
(Kafka, Spark Streaming).
Salary
R60k/month - R150k/month
Culture & Benefits
Collaborative, forward-thinking engineering culture.
Emphasis on
technical excellence
,
ownership
, and
system sustainability
.
Autonomy in decision-making and
mentorship opportunities
.
Chance to shape foundational ML infrastructure for enterprise-scale systems.
Discretionary performance-based bonus.