Senior Data Scientist (ML Engineer) OVA5861

Ovations Talent Sourcing; Johannesburg; Hybrid; ZAR 1,000,000 - 1,300,000; Full time

Job summary

Ovations Talent Sourcing seeks a Senior Machine Learning Engineer for a 12-month contract to operationalize, scale, and manage production-grade ML, AI, and GenAI solutions. You'll focus on building robust MLOps pipelines on Databricks, deploying AI Agents and RAG solutions, and hosting containerized models and microservices on AKS.

Responsibilities include productionizing pipelines, deploying GenAI applications, and optimizing AKS-based deployments with Docker.

Qualifications

• Degree in Computer Science, Engineering, Mathematical Statistics, Actuarial Science, Econometrics, or a quantitative field.
• Strong hands-on experience with Databricks (MLflow, Model Serving) and AKS using Docker/Kubernetes.
• High proficiency in Python, SQL, and REST API development.
• Demonstrated experience building automated CI/CD deployment pipelines, model monitoring, and observability frameworks.
• Experience deploying ML models, LLMs, RAG architectures, and microservices in production.

Responsibilities

• Productionize, automate, and monitor ML pipelines, model serving, and workflows with Databricks, MLflow, and Mosaic AI.
• Build, deploy, and support GenAI applications, AI Agents, and Retrieval-Augmented Generation solutions.
• Deploy and optimize open-source AI models and REST microservices on AKS using Docker and Kubernetes.
• Monitor drift, performance, and costs in production; resolve issues across APIs and pipelines.
• Collaborate with Data Scientists to scale prototypes into enterprise assets.

Skills

Python

SQL

REST API

CI/CD

MLOps

GenAI

Education

Bachelor's degree in Computer Science or related field

Tools

Databricks

MLflow

Mosaic AI

Azure Kubernetes Service (AKS)

Docker

Kubernetes

Job description

Senior ML Engineer (12-Month Contract)

Location: Hybrid

We are seeking a Senior Machine Learning Engineer for a 12-month contract to operationalize, scale, and manage production-grade ML, AI, and GenAI solutions. You will focus on building robust MLOps pipelines on Databricks, deploying AI Agents and RAG solutions, and hosting containerized models and custom microservices on Azure Kubernetes Service (AKS).

Responsibilities include:

• Databricks & MLOps Pipelines: Productionize, automate, and monitor ML pipelines, model serving, and workflows using Databricks, MLflow, and Mosaic AI with full CI/CD practices.
• GenAI & Agent Deployment: Build, deploy, and support enterprise GenAI applications, AI Agents, and Retrieval-Augmented Generation (RAG) solutions.
• Kubernetes & API Engineering: Deploy and optimize open-source AI models and custom REST microservices on Azure Kubernetes Service (AKS) using Docker and Kubernetes.
• Model Observability & Support: Monitor model drift, operational health, performance, and infrastructure costs in production; resolve technical issues across APIs and pipelines.
• Cross-Functional Collaboration: Partner with Data Scientists to transition prototypes into scalable, compliant enterprise assets.

Requirements include:

• Education: Degree in Computer Science, Engineering, Mathematical Statistics, Actuarial Science, Econometrics, or a quantitative field.
• Platform & Containerization: Strong hands-on experience with Databricks (MLflow, Model Serving) and Azure Kubernetes Service (AKS) using Docker and Kubernetes.
• Core Tech Stack: High proficiency in Python, SQL, and REST API development.
• MLOps & CI/CD: Demonstrated experience building automated CI/CD deployment pipelines, model monitoring, and observability frameworks.
• GenAI & Production ML: Practical experience deploying machine learning models, LLMs, RAG architectures, and microservices into live enterprise environments.