Senior AI Specialist

7 days ago

Johannesburg, Gauteng, South Africa Boardroom Appointments Full time R1 200 000 - R2 400 000 per year


Minimum requirements:

  • Advanced Diplomas/National 1st Degrees
  • B.Sc Computer Science, B.Com Informatics, Engineering Degrees (preferred) Candidates should have development experience in generative models such as M365 Co-Pilot, Bing Chat, GitHub Co-Pilot, GPT, and Transformer models. Candidates should identify the use case, define POC generative AI models, and test the models extensively to ensure they meet quality/performance.
  • Proven experience in developing and deploying Gen AI solutions in a real-world setting.
  • Programming skills in languages such as Python, C++ or Java will be advantageous.
  • Understanding of machine learning, deep learning, and natural language processing techniques.
  • Prompt Engineering skills would be an advantage.
  • Furthermore, one should have a good understanding of the ethical, social, and legal implications of developing and deploying Gen AI systems.
  • Excellent problem-solving skills and the ability to work on complex, unstructured problems.
  • Strong communication and presentation skills, with the ability to convey complex AI concepts to non-technical stakeholders.
  • Experience with cloud computing platforms (e.g., AWS, Azure, Google Cloud) is a plus.
  • Experience in leading and mentoring junior team members is a plus.

Technical / Professional Knowledge

  • Technical skills
  • Product management
  • Project Management
  • Financial management
  • Strategy planning and execution
  • Vendor Management Skills
  • Stakeholder management
  • Governance, Risk and Controls
  • Relevant regulatory knowledge

Responsibilities:

  • Gen AI Strategy: Collaborate with the leadership team to define and execute the company's AI strategy, identifying opportunities to leverage Gen AI to drive business growth and innovation.
  • Agile Leadership: Lead Gen AI squads from conception to implementation, ensuring that they are delivered on time and meet the highest quality standards.
  • Algorithm Development: Develop and optimize machine learning and deep learning algorithms to solve complex business problems.
  • Model Training and Evaluation: Build, train, and evaluate Gen AI models using large datasets, continuously improving model performance and accuracy.
  • Mentorship: Provide guidance and mentorship to junior Gen AI team members, fostering their professional growth and development.
  • Research and Innovation: Stay current with the latest Gen AI research and technologies, identifying opportunities to incorporate new advancements into our Gen AI solutions.
  • Cross-functional Collaboration: Work closely with product managers, engineers, and other stakeholders to integrate AI capabilities into our products and services.
  • Ethical AI: Ensure that Gen AI models and solutions adhere to ethical guidelines and data privacy regulations.

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