157 Machine Learning jobs in South Africa

Value Proposition

The Shoprite Group is Africa's largest fast-moving consumer goods retailer with over 35 million customers and 2,500 outlets. Our customers are at the heart of what we do, and our sole purpose is to provide all communities with high quality products at the most affordable prices. Within such a dynamic environment, innovation and the effective application of technology are becoming essential to maintain a competitive position. We continue to invest in being a technologically innovative and enabled business. You will be part of delivering complex machine learning and data solutions to some of the most recognised retail brands in South Africa. You will be surrounded by teams and individuals who challenge you and inspire you to be extraordinary. Are you ready to make an impact?

Role Purpose

The Machine Learning Engineer is an emerging specialist professional who will kick start their careers by supporting the ML team to apply computer science (including data structures, algorithms, computability and complexity) statistical modeling, and software engineering in machine learning operations (MLOps) to build cutting edge, end-to-end ML data models. The role supports the development of solutions and design of self-running and automated software and predictive models to enable the Group increase efficiencies, reduce costs, identify opportunities that generate value and drive data as a competitive advantage.

Role Description

• Participate in stakeholder meetings and work with senior colleagues to analyse business problems, clarify requirements and define the scope of the resolution needed.
• Collaborate within a cross-functional team of Data Scientists, Engineers and Analysts in order to understand project goals, and build, implement and scale-up algorithms for measurable impact.
• Display basic understanding of ANN's, CNN's, RNN's, autoencoders, fundamental data science concepts (linear and logistic regression, SVM's, dimensionality reduction), decision trees, gradient boosting, ensemble models, etc. to develop machine learning models.
• Work with above architectures within deep learning frameworks such as Keras and TensorFlow.
• Demonstrate foundational understanding of relevant applications and / or systems (including, but not limited to, the machine learning algorithms) being created.
• Build basic algorithms based on statistical modelling procedures and build and maintain machine learning solutions in production.
• Use data modelling and evaluation strategy to find patterns and predict unseen instances.
• Train models on large-scale data and fine tune hyper-parameters.
• Research appropriate machine learning algorithms and tools and work with senior colleagues to select the correct libraries, programming languages and frameworks for each task.
• Apply understanding of theoretical frameworks in computer science fundamentals, including data structures, algorithms, computability, complexity and computer architecture.
• Keep abreast of technological developments in the field, and integrate the latest data technologies into existing requirements.
• Follow best practices and standards of machine learning operations (MLOps) workflows for data preparation, deployment, monitoring and retraining to enable agile application methods to projects, and support machine learning models and data sets within a CI / CD process.

Qualifications and Experience

Our Group and all its operating companies is committed to creating, embracing, and preserving a diverse workplace that values the unique talents, perspectives, backgrounds, and abilities that enrich our organisation. A place where everyone matters and feels included.

We are committed to Employment Equity when recruiting internally and externally.

Please take note that by responding to this application and providing your personal information, you confirm your express and informed consent for Shoprite Checkers (Pty) Ltd and all its subsidiaries and affiliates companies to process your personal information for the Company to consider your application for this position. All Personal Information which you provide to the Company will be used and / or retained only for the purposes for which it is collected, whereafter it will be permanently destroyed. Your information is only retained if it is required by law or where you have given consent to us to retain such information for an extended period.

If you don't hear from us within 14 days, please consider your application unsuccessful. Any personal information collected as part of your application will be destroyed, securely, in accordance with South African legislation.

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 Machine Learning Engineer role at Discovery Limited

Join to apply for the Machine Learning Engineer role at Discovery Limited

About Discovery

Discovery’s core purpose is to make people healthier and to enhance and protect their lives. We seek out and invest in exceptional individuals who understand and support our core purpose, and whose own values align with those of Discovery. Our fast-paced and dynamic environment enables smart, self-driven people to be their best. As global thought leaders, Discovery is passionate about innovating in order to not only achieve financial success, but to ignite positive and meaningful change within our society .

Discovery Insure

Machine Learning Engineer

About Discovery

Discovery’s core purpose is to make people healthier and to enhance and protect their lives. We seek out and invest in exceptional individuals who understand and support our core purpose, and whose own values align with those of Discovery. Our fast-paced and dynamic environment enables smart, self-driven people to be their best. As global thought leaders, Discovery is passionate about innovating in order to not only achieve financial success, but to ignite positive and meaningful change within our society .

About Discovery Insure

Discovery Insure is committed to creating a nation of great drivers through our innovative Shared-value Insurance model. Discovery Insure is South Africa’s fastest growing short-term insurance company with comprehensive products that provide protection against current and emerging risks facing clients in the motor and home insurance sectors. Vitality Drive, an internationally-recognised and award-winning programme, is a key differentiator in the market that incentivises and rewards clients for driving well. The Vitality Drive programme has been scaled to local and international markets which now include Europe and the Middle East. The company employs over 1 000 people who are committed to putting our customers and financial advisers first by providing unique and innovative solutions and cover.

Key Purpose

This ML Engineer is responsible for designing, building, managing, and continuously improving the operational processes that support the deployment and maintenance of actuarial, machine learning, and other decision-support models. The role involves end-to-end project planning, cross-functional collaboration with actuarial, data science, analytics, and business teams, and delivering insights into process efficiency across business areas. It also includes reporting on the design, progress, and performance of models and related business processes to drive operational excellence and informed decision-making.

Areas of responsibility may include but are not limited to

• Design and create implementation and testing processes for models in both a traditional and ML framework to ensure business decisions can be actioned quickly and effectively.
• Assist with the design and integration of traditional models and processes into cloud-based platforms like DataBricks to utilise additional functions and better performance.
• Responsible for deploying rating and logic engines using proprietary software, ensuring accurate implementation and seamless integration into production environments.
• Project planning and collaboration with actuarial, data science, underwriting, operational and system teams to ensure a smooth implementation process that reduces risks and achieves the required outcomes.
• Frequent monitoring and reporting on the progress and performance of existing models and processes, as well as presenting the design for new processes to upper management.
• Creation of automated processes and reports to reduce manual intervention and flag any areas of concern as they arise.
• Assessment of the efficiency and effectiveness of business processes through data analytics to identify any areas for improvement or cost savings.
• Implementation of pricing changes in existing models on a frequent basis, to ensure that changes in our pricing structure and strategies can be quickly actioned.
• Creation of new tools and processes that can be used to reduce manual intervention and turnaround time of our client support teams.
  
  

• Modelling skills preferred (Basic)
• Programming Skills: SQL, Python (Intermediate)
• Microsoft Office (Excel, PowerPoint and Word) (Advanced)
  
  

• Matric (Essential)
• Honours degree in Actuarial Science and/or Mathematical Statistics/ Computer Science or Data Science (Essential)
• Min 3-5 completed CT subjects if Actuarial Degree (Advantageous)
  
  

• At least 1-3 years’ experience within a data driven industry
• Experience with Databricks
• Experience with Azure ML solutions
• Experience with WTW Software (e.g., Radar Live) (advantageous)
  
  

• Seniority level Associate

• Employment type Full-time

• Job function Engineering and Information Technology

Referrals increase your chances of interviewing at Discovery Limited by 2x

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We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.

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:

Select how often (in days) to receive an alert:

Business Unit: Discovery Insure

Function: Actuarial Sciences

Date: 24 Jul 2025

Discovery Insure

Machine Learning Engineer

About Discovery

Discovery’s core purpose is to make people healthier and to enhance and protect their lives. We seek out and invest in exceptional individuals who understand and support our core purpose, and whose own values align with those of Discovery. Our fast-paced and dynamic environment enables smart, self-driven people to be their best. As global thought leaders, Discovery is passionate about innovating in order to not only achieve financial success, but to ignite positive and meaningful change within our society .

About Discovery Insure

Discovery Insure is committed to creating a nation of great drivers through our innovative Shared-value Insurance model. Discovery Insure is South Africa’s fastest growing short-term insurance company with comprehensive products that provide protection against current and emerging risks facing clients in the motor and home insurance sectors. Vitality Drive, an internationally-recognised and award-winning programme, is a key differentiator in the market that incentivises and rewards clients for driving well. The Vitality Drive programme has been scaled to local and international markets which now include Europe and the Middle East. The company employs over 1 000 people who are committed to putting our customers and financial advisers first by providing unique and innovative solutions and cover.

Key Purpose

This ML Engineer is responsible for designing, building, managing, and continuously improving the operational processes that support the deployment and maintenance of actuarial, machine learning, and other decision-support models. The role involves end-to-end project planning, cross-functional collaboration with actuarial, data science, analytics, and business teams, and delivering insights into process efficiency across business areas. It also includes reporting on the design, progress, and performance of models and related business processes to drive operational excellence and informed decision-making.

Areas of responsibility may include but are not limited to

• Design and create implementation and testing processes for models in both a traditional and ML framework to ensure business decisions can be actioned quickly and effectively.
• Assist with the design and integration of traditional models and processes into cloud-based platforms like DataBricks to utilise additional functions and better performance.
• Responsible for deploying rating and logic engines using proprietary software, ensuring accurate implementation and seamless integration into production environments.
• Project planning and collaboration with actuarial, data science, underwriting, operational and system teams to ensure a smooth implementation process that reduces risks and achieves the required outcomes.
• Frequent monitoring and reporting on the progress and performance of existing models and processes, as well as presenting the design for new processes to upper management.
• Creation of automated processes and reports to reduce manual intervention and flag any areas of concern as they arise.
• Assessment of the efficiency and effectiveness of business processes through data analytics to identify any areas for improvement or cost savings.
• Implementation of pricing changes in existing models on a frequent basis, to ensure that changes in our pricing structure and strategies can be quickly actioned.
• Creation of new tools and processes that can be used to reduce manual intervention and turnaround time of our client support teams.

Skills and Knowledge:

• Modelling skills preferred (Basic)
• Programming Skills: SQL, Python (Intermediate)
• Microsoft Office (Excel, PowerPoint and Word) (Advanced)

Education and Experience

Education:

• Matric (Essential)
• Honours degree in Actuarial Science and/or Mathematical Statistics/ Computer Science or Data Science (Essential)
• Min 3-5 completed CT subjects if Actuarial Degree (Advantageous)
• At least 1-3 years’ experience within a data driven industry
• Experience with Databricks
• Experience with Azure ML solutions
• Experience with WTW Software (e.g., Radar Live) (advantageous)

EMPLOYMENT EQUITY

The Company’s approved Employment Equity Plan and Targets will be considered as part of the recruitment process. As an Equal Opportunities employer, we actively encourage and welcome people with various disabilities to apply.

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

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

Referrals increase your chances of interviewing at Blue Pearl by 2x

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We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.

Let's build the future together!

Ikue is a tech start-up with a clear purpose and vision - to provide telecommunications operators with a superior product to deliver exceptional customer experiences.

We understand that customer data is at the heart of hyper-personalization and are looking for the brightest, most inspiring engineers to deliver our product, which enables data to drive every decision, communication, and customer interaction.

We are building a diverse team, all unified by a desire to unleash the data needed by marketers. Creativity is at the core of Ikue and is something we aim to further strengthen in 2022! There are no typical profiles; each team member shares our vision and wants to be part of its success.

1. Design and construct Ikue's AI Studio in collaboration with Product Owners and Data Scientists
2. Design and build machine learning pipelines (model development, evaluation, deployment, monitoring)
3. Integrate machine learning outputs into real-time and batch data pipelines
4. Ensure machine learning and data pipelines are monitored, reliable, and supportable (including expert support when required)

• Becoming part of an international environment that embraces diversity and professionalism
• A dynamic and motivated team with a good sense of humor
• Responsibility and growth opportunities within the team
• Work in a fast-paced company
• Remote work model

• BSc in Computer Science or Engineering
• 3+ years of experience as a Machine Learning Engineer
• Advanced skills in Python, Spark, and SQL
• Experience deploying and maintaining machine learning models (e.g., binary classification, regression, clustering) in the cloud (AWS ECS and Sagemaker preferred)
• AWS Associate Developer certification (Machine Learning Specialty preferred)
• Excellent problem-solving and analytical skills
• Strong communication and collaboration abilities

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