Machine Learning Engineer

Reference: PR000894-RN-1

Psybergate is an IT company that builds bespoke software solutions and provides highly skilled resources to its clients. We are looking for a Senior Machine Learning Engineer to join our financial services client based in Sandton for a 12-month contract role.

The successful candidate will be responsible for designing, prototyping, building, deploying, scaling, and supporting next-generation Machine Learning, Artificial Intelligence, and Generative AI solutions in production environments. The role will focus on operationalising models, developing AI applications and agents, and building scalable AI/ML platforms and services. Duties & Responsibilities

What you will be doing

• Design, prototype, build, deploy, and support production-grade Machine Learning, AI, and Generative AI solutions.

• Productionise and monitor Machine Learning models and pipelines using Databricks , including MLflow and Model Serving.

• Develop and deploy AI agents, Generative AI solutions, and Retrieval-Augmented Generation (RAG) applications on Databricks.

• Build reusable Machine Learning pipelines incorporating MLOps, CI/CD, automated testing, monitoring, and governance .

• Deploy and operate open-source AI/ML models on Azure Kubernetes Service (AKS) .

• Develop scalable APIs and microservices for AI/ML solutions using Docker and Kubernetes .

• Monitor model performance, drift, reliability, and overall operational health.

• Partner with Data Scientists to productionise models and translate data science solutions into reliable production services.

• Collaborate with platform engineering, cloud, security, and infrastructure teams to deliver scalable and secure AI/ML solutions.

• Troubleshoot and resolve technical issues across Machine Learning models, pipelines, platforms, and services.

• Optimise solutions for performance, scalability, cost, reliability, and operational efficiency.

• Establish and promote engineering standards, frameworks, and best practices for AI/ML development and deployment.

• Provide technical guidance, coaching, and mentoring to other team members.

• Stay current with emerging Machine Learning, AI, Generative AI, MLOps, and cloud technologies.

• Contribute to the end-to-end delivery of AI/ML solutions, from experimentation and development through to production and ongoing support.

What we are looking for

• A relevant Degree in Computer Science, Engineering, Econometrics, Mathematical Statistics, Actuarial Science, Data Science, or a related field.

• Minimum 5 years’ experience in Machine Learning Engineering, AI Engineering, Data Science, or a closely related field.

• Strong hands-on experience developing, deploying, and supporting Machine Learning and AI solutions in production environments .

• Experience with MLOps, DevOps, software engineering practices, CI/CD, and infrastructure automation .

• Strong programming skills in Python and SQL , with experience developing and consuming REST APIs .

• Hands-on experience with Databricks, MLflow, Model Serving , and cloud-based AI/ML platforms.

• Experience with Azure Kubernetes Service (AKS), Kubernetes, and Docker .

• Strong understanding of Machine Learning model deployment, monitoring, model drift, observability, and production operations .

• Experience with Apache Spark and distributed computing .

• Practical experience with Large Language Models (LLMs), Generative AI, RAG, and AI agents/agentic AI .

• Experience working closely with Data Scientists to operationalise and productionise Machine Learning models.

• Ability to design scalable, reliable, secure, and maintainable AI/ML solutions.

• Strong problem-solving skills and the ability to troubleshoot complex technical issues.

• Ability to communicate complex technical concepts effectively to both technical and business stakeholders.

• Experience within financial services, banking, or another regulated environment would be advantageous.

Preferred Certifications

• Microsoft Azure certifications such as AZ-104, AZ-305, or AI-102 .

• Databricks certifications in Data Engineering, Machine Learning Engineering, or Generative AI Engineering .

• CKA or CKAD Kubernetes certifications.

• Relevant DevOps, MLOps, or Platform Engineering certifications.

• Recognised Machine Learning, Artificial Intelligence, or Data Science certifications.

• AWS or Google Cloud certifications would be advantageous.

Please note that if you do not hear from us within 3 weeks , consider your application unsuccessful.

Please note that most of our positions are remote; however, candidates should reside within travelling distance of the client site, as the working arrangements may change depending on business requirements. Package & Remuneration

Monthly