Machine Learning Engineer

Mind Detect Ltd.; Cape Town; On-site; ZAR 450,000 - 800,000; Full time

Benefits offered by this job

Performance-based bonuses

Medical aid

Retirement fund

Professional development budget

Conference opportunities

Collaborative environment

Work-life balance

On-site amenities

Job summary

WhatJobs Direct in Cape Town, Western Cape, is seeking a Lead Machine Learning Engineer to head the design, development, and deployment of advanced ML models and AI-driven solutions. You will guide a team of engineers and data scientists, shaping our AI roadmap and ensuring integration into products and operations.

The role demands strategic thinking, hands-on expertise, and the ability to translate business needs into actionable ML strategies, with a focus on responsible AI and cutting-edge

Qualifications

• Master's or Ph.D. in Computer Science, AI, Statistics, or related field.
• Extensive experience in developing and deploying production ML models.
• Proficiency in Python and core ML libraries (TensorFlow, PyTorch, Scikit-learn, Keras).
• Strong understanding of ML algorithms (supervised, unsupervised, reinforcement).
• Experience with MLOps tools and practices (MLflow, Kubeflow, Docker, Kubernetes).
• Proven experience in leading technical teams and managing complex projects.
• Excellent data manipulation and analysis skills.
• Familiarity with cloud platforms (AWS, Azure, GCP) and ML services.
• Strong communication, interpersonal, and presentation skills.
• Ability to translate business requirements into actionable ML strategies.

Responsibilities

• Lead end-to-end development lifecycle of ML models from data prep to deployment.
• Design and implement robust MLOps pipelines for CI/CD and monitoring in production.
• Mentor and guide a team of ML engineers and data scientists.
• Collaborate with product, engineering, and business units to identify AI opportunities.
• Research latest ML advances and translate into innovative solutions.
• Develop and maintain scalable ML infrastructure and platforms.
• Ensure ethical and responsible development and deployment of AI systems.
• Conduct rigorous testing and validation of models for accuracy and reliability.
• Present findings and recommendations to technical and non-technical audiences.
• Champion best practices in ML development, reproducibility, and documentation.

Skills

Python

Data analysis

Leadership

Team management

Communication

MLOps

Cloud services

Model deployment

PyTorch/TensorFlow

Education

Master's or Ph.D. in Computer Science/AI/Statistics

Tools

TensorFlow

PyTorch

Scikit-learn

Keras

Docker

Kubernetes

MLflow

Kubeflow

Job description

Explore exciting machine learning engineer opportunities in Cape Town , South Africa. Discover roles focused on developing, implementing, and deploying advanced AI models . This dynamic field offers positions for skilled professionals eager to work with cutting-edge technologies in a growing market. Find your next career move in data science and artificial intelligence within the Western Cape .

Machine Learning Engineers in Cape Town can expect to earn between R450,000 and R800,000 per year. This range can vary based on experience level, specific skills, and the employing company's size and industry. Junior roles may start at the lower end, while senior positions with specialized expertise can command higher salaries.

About the Role Our client, WhatJobs Direct, is seeking an accomplished Lead Machine Learning Engineer to spearhead AI initiatives from their prestigious **Cape Town, Western Cape** office. This senior position involves leading the design, development, and deployment of sophisticated machine learning models and AI-driven solutions that address complex business challenges. You will be at the forefront of innovation, guiding a team of talented engineers and data scientists to push the boundaries of artificial intelligence. The ideal candidate possesses a deep understanding of ML algorithms, a passion for solving real-world problems with data, and proven leadership capabilities. This role demands strategic thinking, hands-on technical expertise, and the ability to translate business requirements into actionable ML strategies. You will play a critical role in shaping our client's AI roadmap, ensuring the successful integration of ML solutions into their product suite and operational processes. We are committed to building a diverse and inclusive team where cutting-edge research meets practical application.

Key Responsibilities

• Lead the end-to-end development lifecycle of machine learning models, from data preprocessing and feature engineering to model training, evaluation, and deployment.
• Design and implement robust MLOps pipelines for continuous integration, delivery, and monitoring of ML models in production.
• Mentor and guide a team of ML engineers and data scientists, fostering a collaborative and high-performance culture.
• Collaborate with stakeholders across product, engineering, and business units to identify opportunities for AI and ML integration.
• Research and stay abreast of the latest advancements in machine learning, deep learning, and AI to identify and implement innovative solutions.
• Develop and maintain scalable ML infrastructure and platforms.
• Ensure the ethical and responsible development and deployment of AI systems.
• Conduct rigorous testing and validation of models to ensure accuracy, reliability, and performance.
• Present findings, progress, and technical recommendations to both technical and non-technical audiences.
• Champion best practices in ML development, reproducibility, and documentation within the Cape Town, Western Cape team.

Requirements

• Master's or Ph.D. in Computer Science, Artificial Intelligence, Statistics, or a related quantitative field.
• Extensive experience in developing and deploying production-grade machine learning models.
• Proficiency in Python and core ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn, Keras).
• Strong understanding of various ML algorithms, including supervised, unsupervised, and reinforcement learning.
• Experience with MLOps tools and practices (e.g., MLflow, Kubeflow, Docker, Kubernetes).
• Proven experience in leading technical teams and managing complex projects.
• Excellent data manipulation and analysis skills.
• Familiarity with cloud platforms (AWS, Azure, GCP) and their ML services.
• Strong communication, interpersonal, and presentation skills.
• Demonstrated ability to work effectively in a collaborative, fast-paced environment.

Benefits

• Highly competitive salary and performance-based bonuses.
• Comprehensive medical aid and retirement fund.
• Generous professional development budget.
• Opportunities to present at conferences.
• Collaborative work environment with industry leaders.
• Focus on work-life balance.
• On-site amenities and social events.
• Relocation assistance may be considered for exceptional candidates.
• Access to state-of-the‑art computing resources.