69 AI Evangelist jobs in South Africa

Lead, Artificial Intelligence & Machine Learning Engineer

Job Overview

Business Segment: Group Functions

Location: ZA, GP, Johannesburg, Baker Street 30

To shape the Standard Bank Group (SBG) artificial intelligence (AI) strategy and drive the creation of AI and machine learning (ML) solutions and projects; prioritising the delivery of new AI initiatives. To apply deep domain expertise in driving the AI strategy to enable SBG to be a business and thought leader in its desired markets.

Qualifications

• Masters Degree in Information Technology
• 8 - 10 Years' experience in the Artificial Intelligence and Machine Learning area

Apply by :

We're on the lookout for energetic, self-motivated individuals who share our passion for service in the banking industry. To be part of the journey, follow the steps below:

1.To see what life at Capitec is all about and complete a short assessment, pleaseclick here!

2. Once you have completed the above finalize your application by clicking apply below.

We appoint energized and motivated people for their potential and continuously look for talented, driven individuals to help us innovate and evolve. That is why we focus on finding the right people for the right jobs. We love what we do because we focus on making a positive difference for our clients and employees. Our company DNA is built around talented and committed teams dedicated to build a brand that we are proud of and earns the trust of our clients.

We are a bank, but we’re much more than that.We believe that banking is about enabling peopleto control their financial lives through banking that is simplified, accessible, affordable and delivered through personal experience. By helping our clients manage their financial lives better, we enable them to live better.

At Capitec, we offer our best by living up to our CEO values in every situation – we always put theClient first, act withEnergy andtakeOwnership.And to support people in being their best,our Employee Value Propositionoffersevery value to all team members through cohesive teams, growth opportunities as well asemployee benefitsand savings. We make it a priority toensure that each member of the Capitec team feels welcome, valued, focused, and has the opportunity to grow.

As a Machine Learning Engineer at Capitec is pivotal in shaping and executing the bank's AI strategy. By collaborating with Data Scientists and Decision Scientists, you'll enhance their efficiency through the development, implementation, and support of platform improvements. Your contributions will be crucial in positioning Capitec to remain competitive in a rapidly evolving landscape where AI technologies are key strategic differentiators.

This role leverages your deep understanding of machine learning models, from concept to deployment, and expertise in modern software development best practices, big data processing frameworks, and cloud environments whilst sitting in the risk division of the business. You’ll also be working extensively with Python, SQL, and advanced debugging techniques to ensure the delivery of scalable, robust, and production-ready predictive models

Our ideal candidate has:

• 4+ years of experience in any engineering role
• Honors degree or higher in any field
• Python and SQL experience
• PySpark
• Big data frameworks – Hadoop/Kafka
• Github experience or Git

Ideal:

• AWS experience

• Simplify and make it easy
• Earn and extend trust
• Plan, deliver and raise the bar
• Curious and continuously learns
• Act, learn and adapt
• Inspire optimism and persistence
• Have courage, disagree and commit

• Completed an Honors Degree or higher

If you are interested in being part of this dynamic team, on a mission to build the best bank in the world through unlocking the potential of its people, please apply. We would love to hear from you!

Capitec is committed to diversity and, where feasible, all appointments will support the achievement of our employment equity goals

Capitec is committed to diversity, applications to this position will strictly be considered in support of our employment equity goals.

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We're on the lookout for energetic, self-motivated individuals who share our passion for service in the banking industry. To be part of the journey, follow the steps below:

1. To see what life at Capitec is all about and complete a short assessment, please click here!

2. Once you have completed the above, finalize your application by clicking apply below.

We appoint energized and motivated people for their potential and continuously look for talented, driven individuals to help us innovate and evolve. That is why we focus on finding the right people for the right jobs. We love what we do because we focus on making a positive difference for our clients and employees. Our company DNA is built around talented and committed teams dedicated to building a brand that we are proud of and that earns the trust of our clients.

We are a bank, but we’re much more than that. We believe that banking is about enabling people to control their financial lives through banking that is simplified, accessible, affordable, and delivered through personal experience. By helping our clients manage their financial lives better, we enable them to live better.

At Capitec, we offer our best by living up to our CEO values in every situation – we always put the Client first, act with Energy, and take Ownership. To support our people in being their best, our Employee Value Proposition offers every value to all team members through cohesive teams, growth opportunities, and employee benefits and savings. We prioritize making each member of the Capitec team feel welcome, valued, focused, and have opportunities to grow.

As a Machine Learning Engineer at Capitec, you will be pivotal in shaping and executing the bank's AI strategy. Collaborating with Data Scientists and Decision Scientists, you'll enhance their efficiency through developing, implementing, and supporting platform improvements. Your contributions will be crucial in positioning Capitec to remain competitive in a landscape where AI technologies are key strategic differentiators.

This role leverages your deep understanding of machine learning models, from concept to deployment, and expertise in modern software development practices, big data processing frameworks, and cloud environments, sitting within the risk division. You’ll work extensively with Python, SQL, and advanced debugging techniques to ensure the delivery of scalable, robust, and production-ready predictive models.

• 4+ years of experience in any engineering role
• Honors degree or higher in any field
• Python and SQL experience
• PySpark
• Big data frameworks – Hadoop/Kafka
• Github experience or Git

• AWS experience
• Ability to simplify complex problems
• Ability to earn and extend trust
• Planning, delivering, and raising the bar
• Curiosity and continuous learning
• Ability to act, learn, and adapt
• Inspiring optimism and persistence
• Courage to disagree and commit

• Completed an Honors Degree or higher

If you are interested in being part of this dynamic team, on a mission to build the best bank in the world by unlocking the potential of its people, please apply. We would love to hear from you!

Capitec is committed to diversity and, where feasible, all appointments will support our employment equity goals.

Applications to this position will be considered in support of our employment equity goals.

Capitec Bank is an authorized financial services provider (FSP 46669) and registered credit provider (NCRCP13). Capitec Bank Limited Reg. No: 1980/003695/06

Melio is seeking a passionate Machine Learning Engineer to join our expanding team:

• Level: Junior or Intermediate
• Position: Full time
• Salary: Based on technical experience

As a fast-paced start-up, our day-to-day is never the same. We look for candidates who love to take up new challenges and have the flexibility to go above-and-beyond the call of duty.

That being said, this specific role is for a team member to work in the Machine Learning AI team as a Machine Learning Engineer.

The candidate will be working with clients on projects focused on delivering reliable data-powered software applications to production. The primary focus of the role includes designing and implementing data pipelines, building models (machine learning or not), and deploying models.

Melio believes in nurturing cross-functional capabilities in our team, so you will need to work closely with other technical roles, such as BI specialists, data scientists, DevOps engineers and other data and machine learning engineers either to observe or to assist.

This is a technical role, but due to the consulting nature of many of our projects, the candidate needs to be able to communicate effectively with both business and technical stakeholders.

The list below is for both machine learning engineer and data engineer, but we are not expecting you to perform as both an ML engineer and a data engineer. The idea is you should be sufficiently comfortable with either role to be aware and able to communicate and learn from your colleagues.

• Fluent with the following languages: Python, Spark, PySpark, SQL.
• Strong analytical skills and passion for solving data problems.
• Strong communications skills and comfortable presenting your own thoughts to technical and business stakeholders.
• Familiar with building training and inference pipelines for ML projects.
• Familiar with fundamental machine learning theory and building, tuning, selecting models.
• Familiar with MLOps principals.
• Some experience with at least one Cloud provider.
• Some experience working with test automation and tools.
• Implement and test data engineering and machine learning software.
• Build and test data engineering and machine learning pipelines for data analytics or machine learning solutions.
• Collaborate and share technical knowledge with team members and co-workers.
• Follow all best practices and procedures as established by the client or industry.
• Document designed solutions and implemented tools.
• Brainstorm new solutions to improve data and ML software development and deployment.
• Basic understanding of the cloud-native ecosystem and desire to learn and grow in this environment.

• Assist with setting up CI (Continuous Integration) and CD (Continuous Delivery) tools with the team.
• Monitor data/model metrics, and develop ways to improve application development and deployment.
• Maintain day-to-day management and administration of projects.

• Bachelor’s degree in Computer Science, Engineering, Software Engineering, Applied Mathematics, Statistics, or related field.
• 2+ years experience working with data science and data engineering. Previous experience with software development (e.g. Python, Java, Go).

Desired Skills

• Contribute and/or passionate about open source projects.
• Masters/PhD in Data Science, Machine Learning or AI.
• AWS certifications (or any other cloud).
• Interested in learning more about Cloud Native Computing Foundation technologies.

• Up-to-date on latest industry trends; able to articulate trends clearly and confidently.
• Able to interact with other team members via code and design documents.
• Good interpersonal skills and communication with all levels of management.
• Able to multitask, prioritize, and manage time efficiently.
• Curious and eager to learn about new technologies.
• Strong in critical thinking and problem-solving.

If you are interested in this position please email Merelda ( ) with the below information:

We are looking for a talented Machine Learning Engineer to join our team, responsible for developing and deploying machine learning models and algorithms that drive business growth and innovation. The successful candidate will have a strong background in machine learning, deep learning, and software engineering, with a proven track record of delivering high-quality machine learning models and algorithms. The Machine Learning Engineer will work closely with cross-functional teams, including data science, product, and engineering, to identify opportunities for machine learning-driven innovation and develop strategic plans to execute on these opportunities.

1. Design, develop, and deploy machine learning models and algorithms that drive business growth and innovation
2. Collaborate with data scientists to develop and implement machine learning models and algorithms
3. Work with software engineers to integrate machine learning models and algorithms into production-ready software applications
4. Develop and maintain large-scale machine learning systems, including data pipelines, model training, and model serving
5. Optimize machine learning models and algorithms for performance, scalability, and reliability
6. Stay up-to-date with the latest advancements in machine learning, deep learning, and AI, applying this knowledge to drive innovation and improvement in machine learning models and algorithms
7. Collaborate with product managers to develop product roadmaps and prioritize features and requirements
8. Develop and maintain relationships with key stakeholders, including business leaders, product managers, and engineering teams
9. Communicate complex machine learning concepts and results to non-technical stakeholders, including business leaders and product managers

1. Bachelor's or Master's degree in Computer Science, Electrical Engineering, or related field
2. 3+ years of experience in machine learning, deep learning, or software engineering, with a focus on machine learning model development and deployment
3. Strong background in machine learning, deep learning, and software engineering, with expertise in areas such as natural language processing, computer vision, or recommender systems
4. Experience with machine learning frameworks and tools, such as TensorFlow, PyTorch, or Scikit-learn
5. Strong programming skills in languages such as Python, Java, or C++
6. Experience with cloud-based technologies, such as AWS or Google Cloud
7. Strong understanding of software engineering principles, including design patterns, testing, and version control
8. Strong communication and collaboration skills, with the ability to work effectively with cross-functional teams

Technical Skills:

1. Machine learning frameworks: TensorFlow, PyTorch, Scikit-learn, etc.
2. Deep learning frameworks: Keras, TensorFlow, PyTorch, etc.
3. Cloud-based technologies: AWS, Google Cloud, Azure, etc.

Full time

Johannesburg

Sandton, South Africa | Posted on 08/28/2024

MUSE  is a consulting company, specialising in resourcing, recruitment and outsourcing of software development teams.

MUSE was founded and is run by experienced developers who are passionate about technology and innovation. We have a vision to be the best in the industry and to provide software development skills that are cutting-edge and high-quality.

We work with some of the leading companies in South Africa and we help them build software products and solutions that are game-changing and future-oriented. We are also at the forefront of applying AI, AR and Machine-Learning concepts to real-world problems.

Our main goal is to help our clients get the most value from their technology investments. We do this by understanding their needs and providing them with the best talent available. We aim to be a vital part of the SDLC.

Are you a talented and enthusiastic Machine Learning Engineer looking for an exciting opportunity? Join our Machine Learning Operations team and be at the forefront of designing, building, testing, deploying, and monitoring cutting-edge machine learning and analytics applications. This role offers the chance to work with state-of-the-art technologies and contribute to the automation of machine learning and AI use cases. Collaborate with data scientists, actuaries, data engineers, and other software engineers to help architect our bank’s modern Machine Learning ecosystem.

Machine Learning Automation and Software Engineering:

• Design, build, and deploy machine learning and analytics automation processes.
  
• Refactor existing code bases to enhance efficiency, robustness, scalability, and automation of machine learning workflows.
  

Cloud-Native Development:

• Utilize Databricks and Azure for data engineering and machine learning use cases.
  
• Leverage Azure services such as Azure Functions, CosmosDB, API Gateway, and Azure Machine Learning to build intelligent data applications.
  

DevOps and Software Engineering:

• Build CI/CD pipelines to improve development and deployment practices.
  
• Develop robust testing and monitoring capabilities for machine learning and AI use cases.
  
• Experience with Git, Jenkins, Azure DevOps, and Terraform is advantageous.
  
• Build APIs to serve machine learning models.
  
• Apply software engineering best practices to develop robust, scalable, and maintainable code.
  
• Create microservice applications using Docker and container orchestration tools like OpenShift.
  
• Collaborate with cross-functional teams to deliver high-quality software solutions for machine learning and data use cases.
  
• Create and maintain documentation of processes, technologies, and code bases.
  
• Familiarity with MLFlow, PyTorch, TensorFlow, etc., is beneficial for the productionization of machine learning use cases.
  
• Work closely with data scientists, actuaries, data engineers, and other software engineers to understand and address their data needs.
  
• Contribute actively to the architecting of our bank’s modern Machine Learning data ecosystem.
  

• 1-3 years of experience as a Software Engineer.
  
• Bachelor’s degree in engineering or a related field. Other qualifications will be considered if accompanied by sufficient experience in software engineering.
  

• 2 years of experience using Python and SQL.
  
• Exposure to Linux shell scripting is advantageous.
  
• Experience with Spark is advantageous.
  
• Interest in software architecture.
  
• Knowledge of cloud compute services.
  
• Familiarity with serverless computing and cloud-native development.
  
• Keen interest in systems design and software architecture.
  
• Knowledge of machine learning frameworks/packages (e.g., MLFlow, Spark ML, Sklearn).
  
• Understanding of CI/CD concepts and API development, with implementation experience being advantageous.
  
• Strong critical thinking, problem-solving, and collaboration skills.
  
• Ability to collaborate with cross-functional tech teams as well as business/product teams.
  
• Commitment to excellence and high-quality delivery.
  
• Passion for personal development and growth, with a high learning potential.
  

If you’re passionate about machine learning and eager to work in a dynamic and innovative environment, we’d love to hear from you! Apply now and be part of our journey to revolutionize the banking industry with cutting-edge AI and machine learning solutions.

Join to apply for the AI Machine Learning role at Blue Pearl

Join to apply for the AI Machine Learning role at Blue Pearl

Job Description

Standard Bank is seeking a highly skilled AI and Machine Learning Specialist to join our innovative team. In this role, you will leverage your expertise in artificial intelligence and machine learning to develop and implement cutting-edge solutions that drive business value and enhance customer experiences.

Job Description

Standard Bank is seeking a highly skilled AI and Machine Learning Specialist to join our innovative team. In this role, you will leverage your expertise in artificial intelligence and machine learning to develop and implement cutting-edge solutions that drive business value and enhance customer experiences.

Responsibilities

• Model Development:
• Design, develop, and train machine learning models.
• Implement AI algorithms and frameworks.
• Conduct exploratory data analysis to inform model development.
• Model Deployment and Integration:
• Deploy machine learning models into production environments.
• Integrate models with existing systems and data pipelines.
• Ensure seamless operation of deployed models.
• Data Preparation and Feature Engineering:
• Prepare and clean data for model training and evaluation.
• Perform feature engineering to enhance model performance.
• Implement data preprocessing and transformation pipelines.
• Model Evaluation and Tuning:
• Evaluate model performance using appropriate metrics.
• Tune hyperparameters and optimize model accuracy.
• Conduct A/B testing and validation of models.
• Collaboration and Stakeholder Engagement:
• Work with data scientists, engineers, and business stakeholders to understand requirements.
• Translate business problems into technical solutions.
• Communicate findings and model performance to non-technical stakeholders.
• Research and Innovation:
• Stay updated with the latest advancements in AI and ML.
• Experiment with new algorithms and techniques.
• Propose innovative solutions to business problems.
• Documentation and Reporting:
• Document model development processes and methodologies.
• Create user guides and technical documentation.
• Report on model performance and project progress.
  
  

• Machine Learning Models:
• Trained and validated ML models.
• Model deployment scripts and integration guidelines.
• Documentation of model architecture and training processes.
• Data Pipelines:
• Data preprocessing and transformation pipelines.
• Feature engineering scripts.
• Documentation of data preparation steps.
• Performance Reports:
• Model performance metrics and evaluation reports.
• Hyperparameter tuning and optimization logs.
• A/B testing and validation results.
• Technical Documentation:
• User guides for deployed models.
• Technical documentation for model development and deployment.
• Maintenance and monitoring procedures.
  
  

• Seniority level Entry level

• Employment type Full-time

• Job function Engineering and Information Technology
• Industries IT Services and IT Consulting

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