AI/ML Engineer (CPT)

DataFin; Cape Town; On-site; ZAR 600 000 - 800 000; Full time

Job summary

A prominent asset management firm in Cape Town is seeking an experienced AI/ML Engineer to design and deploy end-to-end AI solutions. You will work closely with teams to develop AI models, optimize performance, and ensure system integration. The ideal candidate has 3+ years in AI/ML Engineering, is proficient in Python, and has knowledge of popular frameworks like TensorFlow and PyTorch. This position offers an opportunity to innovate in a dynamic environment.

Qualifications

• 3+ years in AI/ML Engineering or Data Engineering roles.
• Proficiency in Python; familiarity with Java or R.
• Understanding of Machine Learning frameworks.
• Experience with data preprocessing and model evaluation.

Responsibilities

• Transform requirements and build AI solutions.
• Design and develop integrations with AI technologies.
• Deploy AI models and ensure stability.
• Monitor and evaluate performance of deployed models.

Skills

Proficiency in Python

Familiarity with Java or R

Understanding of Machine Learning frameworks

Experience with Big Data frameworks

Hands-on with cloud ML services

Strong problem-solving skills

Tools

PyTorch

TensorFlow

LangChain

Docker

Kubernetes

Azure

Job description

ENVIRONMENT

AN innovative Independent Asset Management Firm seeks to fill the critical role of an AI/ML Engineer who will design, develop, and deploy end-to-end AI/ML solutions and data pipelines that turn raw data into actionable insights, ensuring performance, scalability, and security. Working closely with cross-functional teams, you will help develop and deploy AI solutions, models and systems. Your role will involve researching, prototyping, and integrating cutting-edge AI technologies to solve complex business problems. Applicants will need 3+ years in AI/ML Engineering or Data Engineering roles, with end-to-end delivery with proficiency in Python, familiarity with Java or R. You will also be required to have a solid understanding of Machine Learning frameworks such as LangChain, PyTorch, Tensorflow or Hugging Face.

DUTIES

• Transform requirements and build into AI solutions – Collaborate with Data Scientists, Software Engineers, and business stakeholders to define use cases and architecture for ML systems.
• Design and develop integrations with AI/ML technologies and data sources to leverage solutions for use cases.
• Work with AI/ML partners and internal teams to optimize and fine-tune AI models and use cases for performance, scalability, and accuracy.
• Deploy AI models and use cases into production environments, ensuring stability, reliability, and security.
• Monitor and evaluate the performance of deployed models and use cases, ensuring iterative improvements.
• Collaborate with Software Engineers to integrate AI/ML capabilities into existing or new software systems.
• Stay updated with the latest advancements in AI and Machine Learning research and apply relevant techniques to solve business challenges.
• Document and communicate AI solutions, methodologies, and best practices to technical and non-technical stakeholders.

BUILD SCALABLE DATA PIPELINES

• Design, implement, and maintain data ingestion, preprocessing, and feature-engineering workflows using Big Data frameworks (Spark, Hadoop) and SQL expertia.ai.

DEVELOP AND OPTIMIZE MODELS

• Research, prototype, and productionize ML algorithms with Python and frameworks such as PyTorch, TensorFlow, LangChain, or Hugging Face.
• Implement AI solutions using programming languages (such as Python) and Machine Learning frameworks (such as LangChain, PyTorch, Tensorflow or Hugging Face).
• Support Data Scientists and other stakeholders with collecting, processing, and analysing datasets to train and validate AI models.

DEPLOY AND MONITOR IN THE CLOUD

• Containerize and orchestrate workloads (Docker, Kubernetes) and deploy models on Azure ensuring reliability and cost efficiency.

ENSURE GOVERNANCE & SECURITY

• Implement data quality checks, versioning, and security best practices throughout ML pipelines in line with InfoSec standards.

REQUIREMENTS

• 3+ Years in AI/ML Engineering or Data Engineering roles, with end-to-end delivery.
• Proficiency in Python; familiarity with Java or R.
• Understanding of Machine Learning frameworks such as LangChain, PyTorch, Tensorflow or Hugging Face.
• Experience with data preprocessing, feature engineering, and model evaluation techniques.
• Familiarity with Big Data processing frameworks (such as Hadoop or Spark) and SQL.
• Experience with Databricks and Mosaic.
• Hands-on with cloud ML services (e.g., SageMaker, Azure ML) and CI/CD pipelines for model deployment.

ADVANTAGEOUS

• Knowledge of cloud platforms (such as AWS, Azure, or Google Cloud) and experience with deploying AI models on cloud infrastructure.

ATTRIBUTES

• Ability to adapt to a fast-paced, dynamic work environment and quickly learn new technologies and techniques.
• Curiosity to learn about Artificial Intelligence, Machine Learning, Deep Learning concepts and data insights engines.
• Strong problem-solving and analytical skills, with the ability to understand complex business requirements and translate them into AI solutions.
• Able to explain complex technical concepts to both technical and non-technical audiences.