50 Machine Learning jobs in 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

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Johannesburg, Gauteng, South Africa 4 days ago

Johannesburg, Gauteng, South Africa 2 months ago

Johannesburg, Gauteng, South Africa 1 day ago

Johannesburg, Gauteng, South Africa 4 days ago

Germiston, Gauteng, South Africa 4 days ago

Johannesburg, Gauteng, South Africa 1 month ago

Johannesburg, Gauteng, South Africa 13 hours ago

Johannesburg, Gauteng, South Africa 4 days ago

Sandton, Gauteng, South Africa 2 days ago

Johannesburg Metropolitan Area 1 week ago

Johannesburg, Gauteng, South Africa 2 days ago

Johannesburg, Gauteng, South Africa 1 month ago

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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

• Exposure to the latest AI tools and frameworks (LangChain, Llama-Index, and Vector Databases).
• Opportunity to deploy real-world GenAI solutions that drive tangible business outcomes.
• Collaborative, forward-thinking environment where your input shapes strategy.
• Commitment to equity and inclusion African and Coloured candidates are strongly encouraged to apply.

• Design, implement, and optimize Generative AI solutions and RAG frameworks.
• Develop scalable data pipelines, perform ETL, and design dimensional models for optimal data storage.
• Deploy, monitor, and optimize AI models for performance, scalability, and cost efficiency.
• Collaborate with cross-functional teams to align solutions with business goals.
• Communicate complex AI concepts clearly to non-technical stakeholders.
• Stay ahead of the curve by researching and experimenting with new AI architectures and techniques.

• Education: Bachelors Degree in Computer Science, Data Science, Machine Learning, or a related field (Masters/PhD preferred).
• Experience: 3+ years in AI/ML, with at least 12 years specialising in Generative AI.
• Technical Skills:
  
  • Proficiency in Python, SQL, Pandas, and NumPy.
  • Experience with deep learning frameworks (TensorFlow and PyTorch) and LLM tools (LangChain and Llama-Index).
  • Cloud platforms (AWS, GCP, and Azure) and containerization (Docker and Kubernetes).
  • Strong data engineering skills (ETL, pipeline design, and data modelling).
  • Knowledge of MLOps practices for model versioning, monitoring, and retraining.
• Soft Skills: Proactive, curious, collaborative, and strong communicator.
• Preferred Certifications: AWS ML Specialty, GCP ML Engineer, Azure AI Engineer, or similar.

Position Summary: The Senior Machine Learning Engineer will play a key role in leading the design, development, and deployment of machine learning solutions. You will collaborate with cross-functional teams to identify business opportunities, develop innovative machine learning models, and implement scalable solutions that drive business value. This role offers a unique opportunity to leverage your expertise in machine learning to tackle challenging problems, mentor junior team members, and contribute to the success of our organization.

Key Responsibilities:

• Lead the design, development, and deployment of machine learning models and algorithms to solve complex business problems.
• Collaborate with data scientists, software engineers, and product managers to identify business opportunities and requirements.
• Conduct exploratory data analysis, feature engineering, and model evaluation to ensure robust and reliable performance.
• Implement scalable and efficient machine learning pipelines and workflows to process large volumes of data.
• Stay up-to-date with the latest developments in machine learning research and technologies, and apply them to improve our products and services.
• Mentor and coach junior machine learning engineers, providing guidance, training, and support to develop their technical skills and knowledge.
• Collaborate with cross-functional teams to integrate machine learning models into production systems and applications.
• Document work processes, methodologies, and best practices to facilitate knowledge sharing and collaboration.

Qualifications:

• Master's or Ph.D. degree in Computer Science, Statistics, Mathematics, or a related field (or equivalent experience).
• 5+ years of experience in machine learning engineering or related roles, with a proven track record of developing and deploying machine learning solutions in production environments.
• Strong proficiency in machine learning algorithms, techniques, and frameworks such as TensorFlow, PyTorch, scikit-learn, or Spark MLlib.
• Experience with big data technologies and platforms such as Hadoop, Spark, or Apache Flink.
• Proficiency in programming languages such as Python, Java, or Scala.
• Excellent analytical and problem-solving skills, with a strong attention to detail.
• Excellent communication and collaboration skills, with the ability to effectively work with cross-functional teams.
• Demonstrated leadership and mentoring abilities, with a passion for developing and empowering team members.

• Develop & Enhance AI Models: Create, refine, and implement Generative AI systems and Retrieval-Augmented Generation (RAG) pipelines using frameworks like LangChain and Llama-Index.
• Data Engineering: Build scalable data workflows, manage ETL processes, and integrate both structured and unstructured data for AI-driven applications.
• Production Deployment: Deliver models into production, collaborating with DevOps to ensure performance across cloud and on-prem environments.
• Collaborate Across Teams: Work closely with Engineers, product owners, and business leaders to ensure AI solutions drive measurable value.
• Innovate & Research: Stay current with emerging architectures, frameworks, and methodologies, contributing to innovation and thought leadership.

• Education:
  • Degree in Computer Science, Data Science, Machine Learning, or a related field.
• Experience:
  • 3+ years of professional experience in AI/ML, including at least 12 years in Generative AI.
  • Practical experience with deep learning frameworks (TensorFlow and PyTorch) and generative AI libraries.
  • Familiarity with cloud platforms (AWS, GCP, and Azure) and container technologies (Docker and Kubernetes).
• Skills:
  • Strong programming ability in Python and SQL, plus experience with libraries like Pandas and NumPy.
  • Solid understanding of machine learning algorithms, neural networks, and generative models.
  • Knowledge of large-scale data storage (Hadoop, Spark, and Vector databases).
  • Understanding of MLOps practices, including model lifecycle management, monitoring, and retraining.

• Develop & Enhance AI Models: Create, refine, and implement Generative AI systems and Retrieval-Augmented Generation (RAG) pipelines using frameworks like LangChain and Llama-Index.
• Data Engineering: Build scalable data workflows, manage ETL processes, and integrate both structured and unstructured data for AI-driven applications.
• Production Deployment: Deliver models into production, collaborating with DevOps to ensure performance across cloud and on-prem environments.
• Collaborate Across Teams: Work closely with Engineers, product owners, and business leaders to ensure that AI solutions drive measurable value.
• Innovate & Research: Stay current with emerging architecture, frameworks, and methodologies, contributing to innovation and thought leadership.

• Education: Degree in Computer Science, Data Science, Machine Learning, or a related field.
• Experience:
  • 3+ years of professional experience in AI/ML, including at least 12 years in Generative AI.
  • Practical experience with deep learning frameworks (TensorFlow and PyTorch) and generative AI libraries.
  • Familiarity with cloud platforms (AWS, GCP, and Azure) and container technologies (Docker and Kubernetes).
• Skills:
  • Strong programming ability in Python and SQL, plus experience with libraries like Pandas and NumPy.
  • Solid understanding of machine learning algorithms, neural networks, and generative models.
  • Knowledge of large-scale data storage (Hadoop, Spark, and Vector databases).
  • Understanding of MLOps practices, including model lifecycle management, monitoring, and retraining.

At LexisNexis we develop the legal profession's most innovative products for data analysis, visualization, and research. We use the latest techniques in AI, machine learning, and data visualization to uncover insights about legal matters, contracts and legal spend management.

We are looking for a skilled LLM Application Developer to join our team. You will be responsible for implementing large language model (LLM) based applications, working with proprietary and open-source models as well as popular frameworks such as LangChain or LlamaIndex to ensure seamless integration and deployment.

Responsibilities

• Manage a team of Machine Learning Engineers and Data Engineers
• Collaborate with stakeholders like Product Managers, Data Scientists and Program Managers
• Develop and implement LLM-based applications.
• Fine-tune and deploy large language models.
• Implement production quality ETL jobs
• Build RAG-based applications
• Integrate models with existing systems and APIs.
• Preprocess and manage data for training and deployment.
• Collaborate with cross-functional teams to define, design, and ship new features.
• Write clean, maintainable, and efficient code.
• Document development processes, code, and APIs.

Requirements

• Prior experience managing an engineering team
• Proven experience with large language models and open-source frameworks.
• Experience leveraging models from repositories such as Hugging Face
• Experience with deep learning frameworks such as PyTorch, Tensorflow and Hugging Face Transformers.
• Strong knowledge of API integration (RESTful, GraphQL).
• Experience with data preprocessing, SQL, and NoSQL databases as well as vector stores (e.g., Postgres, Elasticsearch/OpenSearch, ChromaDB etc.)
• Experience with GPU programming, including CUDA or RAPIDs
• Familiarity with deployment tools (Docker, Kubernetes).
• Excellent problem-solving and communication skills.
• Ability to work collaboratively in an agile team environment.

Preferred Qualifications

• Degree in Computer Science, Data Science, or related field.
• Certifications in machine learning, data science, or cloud computing.
• Portfolio showcasing past projects or contributions to open-source projects.