142 AI Ml Engineer jobs in South Africa

Voyc AI Cape Town, Western Cape, South Africa

Voyc AI Cape Town, Western Cape, South Africa

2 days ago Be among the first 25 applicants

This range is provided by Voyc AI. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

ZAR780,000.00/yr - ZAR1,000,000.00/yr

At Voyc, we're building solutions to help financial services companies better understand and manage their customer interactions. As we continue to grow, we're looking for a talented Machine Learning Engineer to join our team and develop features that empower our customers to make informed decisions.

In this role, you'll work on impactful projects that shape the future of our platform and deliver actionable, data-driven insights. You'll be part of a team that pushes the boundaries by integrating natural language processing (NLP) and large language models (LLMs) to refine and expand our machine learning systems.

The ideal candidate will bring expertise in machine learning, programming, and automation in real-world applications. This is a unique opportunity to work on cutting-edge technologies, optimise text-based machine learning models, and contribute to a high-impact, fast-growing SaaS platform.

The Role

As an ML & AI Engineer, you will leverage advanced artificial intelligence, machine learning, and data science techniques to support autonomous data-driven decision-making processes and deliver personalised customer experiences across our platform.

You will design, develop, and deploy a range of AI and ML products and features, using LLMs and other analytical and predictive AI solutions. You'll collaborate with Product, Engineering, and Data Science teams to enhance the platform's AI capabilities, improve model performance, and build scalable machine learning solutions.

Key Responsibilities

ML & NLP Model Development

• Develop, enhance, and deploy NLP models for classification, insights extraction, prioritisation, and recommendation systems
• Design and implement ML algorithms for structured and unstructured data to improve decision-making, accuracy, and automation
• Ensure compliance with legal and ethical standards in AI and data handling practices
  
  

• Expand the functionality and reliability of our LLM and interactive AI assistant through advanced prompt engineering techniques
• Integrate Retrieval-Augmented Generation (RAG), and semantic search and full text search databases to optimise data extraction from large datasets
  
  

• Architect, implement, and manage scalable containerised environments and CI/CD pipelines for ML model deployment
• Monitor and track model performance, optimisation, inference latency, and scalability
  
  

• Collaborate closely with Product, Data Science, and Engineering teams to define AI requirements and deliver effective solutions
• Continuously evaluate emerging AI/LLM technologies and prototype innovative NLP solutions to enhance product capabilities
  
  

• Bachelor Degree in a Science or Engineering discipline
• At least 5 years of experience in machine learning and generative AI feature development, with expertise in NLP
• Experience developing and deploying NLP models for text and token classification, sentence similarity, anomaly detection, and text generation
• An understanding of transformer-based architectures and experience with the HuggingFace ecosystem and AI/ML frameworks (e.g., TensorFlow, PyTorch)
• Strong understanding of MLOps practices, including experiment tracking, model versioning, and cloud-based deployments (AWS preferred)
• Ability to develop innovative and scalable ML/AI solutions that are business-ready
  
  

• Demonstrated ability to implement ML workflows at scale, particularly using LLMs, in a SaaS or enterprise environment
• Experience in handling, analysing, and extracting insights from large and complex datasets, particularly noisy text data
• Previous experience tuning open source and proprietary large language models
• Prior experience mentoring or leading junior ML engineers
  
  

• Remuneration: R780 000 to R1million per year, depending on experience
• Option to participate in our share options program
• A supportive, growth-oriented team culture that aligns with your personal goals
• Flexible working hours
• Innovative leave policies
• Company-sponsored lunches, travel, and learning opportunities, including an annual offsite event in Cape Town and Travel to the Netherlands
• An inclusive and representative workplace
  
  

• Seniority level Mid-Senior level

• Employment type Full-time

• Industries IT Services and IT Consulting

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Job category: FMCG, Retail, Wholesale and Supply Chain

Location: Cape Town

Contract: Permanent

Remuneration: Market Related

EE position: No

The AI/ML Engineer will be responsible for operationalizing AI/ML models developed by the Data Science team, ensuring their seamless integration into production environments. This role focuses on deploying, monitoring, and maintaining AI/ML models, optimising system performance, and automating MLOps processes to enhance scalability and reliability.

• Deploy and operationalize AI/ML models developed by the Data Science team into scalable production environments.
• Develop and maintain robust machine learning pipelines to enable efficient model inference and data transformation.
• Ensure seamless integration of AI/ML models with enterprise applications and data systems.
• Implement MLOps best practices, including CI/CD for machine learning, model versioning, monitoring, and automated retraining.
• Optimize AI/ML workflows for performance, cost efficiency, and resilience.
• Collaborate with data engineers to ensure data pipelines support AI/ML model inference and training.
• Leverage cloud-based AI/ML services (AWS SageMaker, Lambda, Glue, etc.) to streamline model deployment and automation.
• Implement AI-driven monitoring and alerting mechanisms to detect model drift and performance degradation.
• Work closely with business stakeholders to ensure AI/ML models are delivering expected value.
• Ensure AI/ML solutions adhere to best practices for security, compliance, and governance.
• Provide technical support and troubleshoot AI/ML model issues in production environments.
• Bachelor’s degree in computer science, Engineering, or a related field with 4 - 5 years of experience in operationalising AI/ML models in production environments.
• Strong understanding of AI/ML deployment strategies, including containerization, orchestration, and inference optimisation.
• Experience with implementing MLOps principles, including CI/CD pipelines, automated model monitoring, and retraining.
• Proficiency in Python, with experience in AI/ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
• Expertise in data engineering tools and frameworks such as Apache Spark, AWS Glue, and SQL.
• Practical experience with AWS services, including SageMaker, Lambda, S3, IAM, and RDS.
• Experience working with structured and unstructured data within enterprise environments.
• Strong software development skills, with experience in version control systems such as Git.
• Familiarity with containerisation and orchestration tools (Docker, Kubernetes) for AI/ML workloads.
• Knowledge of cloud security, data governance, and compliance considerations.
• Excellent verbal and written communication skills; must work well in an agile, collaborative team environment.

ADDITIONAL CRITERIA

• Analytical Mindset: Strong problem-solving ability to optimise AI/ML deployment and system performance.
• Collaboration and Communication: Ability to work closely with data scientists, data engineers, and business stakeholders to ensure seamless AI/ML integration.
• Continuous Learning: Commitment to staying updated on the latest MLOps trends, tools, and automation techniques.
• Innovative Thinking: Proactive in identifying and implementing AI-driven automation and model optimisation improvements.
• Adaptability: Ability to manage multiple AI/ML model deployments and adapt strategies in a fast-paced environment.
• Cultural Fit: Aligns with the organisation’s values, demonstrating integrity, accountability, and a strong work ethic.