AI Engineer

Introduction

Our Client a Leader within the Healthcare industry based in Sandton requires an AI Engineer.

This is a hybrid role.

The AI Engineer is responsible for designing, building, deploying, and maintaining advanced AI and machine-learning systems with a focus on cloud platforms, MLOps, LLMOps, and modern scalable cloud architectures. The role leads the full lifecycle of AI products including solution design, feature engineering, model development, deployment, monitoring, governance, and optimisation across classical ML and LLM solutions.

Duties & Responsibilities • Knowledge and understanding of the Data Science Development Cycle: business understanding, data profiling, feature derivation and selection, data modelling, model evaluation, productionisation, monitoring. • Ability in applying statistical machine learning techniques to predictive modelling problems and translating this into business solutions. • Ability to clean and unify messy and complex data sets for easy access and analysis. Combining structured and unstructured data. • Ability to provide detailed explanations (visually and verbally), representing information in the form of a chart, diagram, picture, using tools such as Kibana, Tableau, Power BI, etc. • Write programming code in python and SQL based on a prepared design. • Understand leading edge technologies and best practice around Big Data, platforms and distributed data processing i.e. Hadoop ecosystem (distributed computational power)-HDFS/Spark/Kafka. • Ability to conceptualise and frame a problem, develop hypothesis and identify objective measures to estimate accuracy of machine learning/statistical processes and perform testing and validation with careful experiments. • Understanding of data flows, ETL and processing of structured and unstructured data within the data architecture. • Comprehensive solution design based on a good understanding of the Big Data Architecture. • Proficiency with AI platforms and ecosystems: Mosaic AI Vector Search, Model Serving, MLflow, Unity Catalog, Delta Lake, Foundation Model APIs.

Desired Experience & Qualification • Degree (Honours, Masters or PHD) in Data Science, Statistics, Computer Science, Engineering, Mathematics and / or a combination of these or related fields. • Relevant data science and engineering certifications such as Python, Microsoft, AWS, Hadoop, big data, machine learning, databricks and similar cloud infrastructure and platforms. • 7–10+ years in applied machine learning or AI engineering • strong experience with Databricks, MLflow, classical ML and LLM operationalization • Python/SQL; big data systems; cloud production environments. • Experience with Python/Microsoft ML and tools available within the machine learning ecosystem (i.e.numpy, pandas, matplotlib, SciPy stack) and working in Jupyter notebooks. • Experience with SQL and working with large-scale data sets. • Knowledge and practical experience applying machine learning techniques. • Experience working in agile development teams. • Experience in operationalising data science solutions or similar product development. • Experience in a high-scale production environment is critical. • Deep expertise in AI engineering, MLOps and LLMOps best practices.

Apply/send CV to: cv@asie.co.za

Subject Line: AI Engineer

Interested?

Apply/send CV to: cv@asie.co.za

Subject Line: AI Engineer