Ai/Ml Operations (Mlops) Engineer

Placements24; East London; On-site; ZAR 900,000 - 1,300,000; Full time

Job summary

Placements24 is seeking an experienced AI Specialist focused on Data Engineering and ML Operations to join the team in East London, Eastern Cape. The role centers on building robust data pipelines, implementing MLOps best practices, and ensuring seamless deployment and management of AI/ML models in production.

You will enable data science and engineering teams to develop and deploy at scale. The ideal candidate has strong data engineering fundamentals, MLOps experience, and cloud infrastructure

Qualifications

• Bachelor’s degree in CS, Engineering or related field.
• Proven experience in data engineering, MLOps in AI/ML context.
• Strong Python proficiency.
• Experience with cloud platforms (AWS, Azure, GCP).
• Docker and Kubernetes experience.
• Familiarity with ML frameworks (TensorFlow, PyTorch, Scikit-learn) and MLOps tools (MLflow, Kubeflow).
• SQL/NoSQL databases and data warehousing concepts.
• Airflow for data pipeline orchestration.
• Strong problem-solving, analytical and troubleshooting skills.
• Excellent communication and collaboration abilities.

Responsibilities

• Design, build, and maintain scalable data pipelines for AI/ML applications.
• Implement and manage MLOps processes for deployment, monitoring and lifecycle management.
• Develop and automate CI/CD workflows for ML models.
• Manage cloud infrastructure for AI/ML workstreams (AWS/Azure/GCP).
• Ensure data quality, integrity, and accessibility for data science teams.
• Collaborate with data scientists and software engineers to productionize models.
• Monitor deployed models for performance, drift and anomalies; retrain as needed.
• Infrastructure for model training and serving.
• Contribute to data governance and security policies.

Skills

Python programming

Problem solving

Communication

Team collaboration

Education

Bachelor's degree in CS/Engineering

Tools

Docker

Kubernetes

TensorFlow

PyTorch

Scikit-learn

MLflow

Kubeflow

Airflow

SQL/NoSQL

AWS

Azure

GCP

Job description

AI Specialist - Data Engineering & ML Operations

Our client, a leader in AI & Emerging Technologies , is seeking an experienced AI Specialist with a strong focus on Data Engineering and ML Operations (MLOps) to join their dynamic team in East London, Eastern Cape . This critical role involves building and maintaining robust data pipelines, implementing MLOps best practices, and ensuring the seamless deployment and management of AI/ML models in production. You will be instrumental in enabling our data science and engineering teams to develop and deploy models efficiently and at scale. This is an exciting opportunity to work with cutting-edge technologies, contribute to impactful AI initiatives, and grow your career in a supportive and innovative environment. The ideal candidate will possess a strong understanding of data engineering principles, MLOps methodologies, and cloud infrastructure, coupled with excellent problem-solving skills.

About the Role

Our client, a leader in AI & Emerging Technologies , is seeking an experienced AI Specialist with a strong focus on Data Engineering and ML Operations (MLOps) to join their dynamic team in East London, Eastern Cape . This critical role involves building and maintaining robust data pipelines, implementing MLOps best practices, and ensuring the seamless deployment and management of AI/ML models in production. You will be instrumental in enabling our data science and engineering teams to develop and deploy models efficiently and at scale. This is an exciting opportunity to work with cutting-edge technologies, contribute to impactful AI initiatives, and grow your career in a supportive and innovative environment. The ideal candidate will possess a strong understanding of data engineering principles, MLOps methodologies, and cloud infrastructure, coupled with excellent problem-solving skills.

Key Responsibilities

• Design, build, and maintain scalable and reliable data pipelines for AI/ML applications.
• Implement and manage MLOps processes for model deployment, monitoring, and lifecycle management.
• Develop and automate CI/CD workflows for machine learning models.
• Manage and optimize cloud infrastructure for AI/ML workloads (e.g., AWS, Azure, GCP).
• Ensure data quality, integrity, and accessibility for data science teams.
• Collaborate with data scientists and software engineers to productionize machine learning models.
• Monitor deployed models for performance, drift, and anomalies, implementing necessary retraining or adjustments.
• Implement and manage infrastructure for model training and serving.
• Contribute to the development of data governance and security policies.
• Stay up-to-date with the latest tools and best practices in data engineering and MLOps.

Requirements

• Bachelor's degree in Computer Science, Engineering, or a related field; Master's degree is a plus.
• Proven experience in data engineering, MLOps, or a related role within an AI/ML context.
• Strong proficiency in programming languages such as Python.
• Experience with cloud platforms (AWS, Azure, GCP) and their data/ML services.
• Hands-on experience with containerization technologies like Docker and orchestration tools like Kubernetes.
• Familiarity with ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and MLOps tools (e.g., MLflow, Kubeflow).
• Solid understanding of database technologies (SQL/NoSQL) and data warehousing concepts.
• Experience with data pipeline orchestration tools (e.g., Airflow).
• Excellent problem-solving, analytical, and troubleshooting skills.
• Strong communication and collaboration abilities.

Benefits

Our client offers a competitive salary, commensurate with experience, and a comprehensive benefits package including health, retirement, and performance bonuses. We provide a stimulating and collaborative work environment in East London, Eastern Cape , with access to advanced tools and technologies. Opportunities for continuous learning and professional development, including training and conference attendance, are provided. We foster a healthy work-life balance with flexible working arrangements and generous paid time off. Join a team at the forefront of AI innovation, where your expertise in data engineering and MLOps will be crucial to our success.