Job Summary:

The GenAI Solutions Engineer plays a crucial role in the design, development, and deployment of AI-driven applications, including large language models (LLMs) and text-to-image systems. This position requires a strong understanding of AI infrastructure, model optimization, and collaboration with cross-functional teams to deliver innovative solutions. The engineer will be responsible for ensuring the scalability, accuracy, and efficiency of AI models in alignment with organizational goals.

Job Responsibilities:

• AI Application Development and Deployment: Design, develop, and implement AI models and algorithms, including large language models and text-to-image systems, to address complex business challenges.
• Integration and Optimization: Integrate AI solutions into existing business systems, and continuously monitor and optimize AI models for speed, scalability, and accuracy.
• Infrastructure Maintenance: Maintain and troubleshoot infrastructure systems, including servers, networks, and storage, ensuring scalability and security.
• Collaboration: Work with cross-functional teams, including data scientists, software engineers, and project managers, to integrate AI solutions and shape AI/ML strategy.
• Technical Support and Documentation: Provide technical guidance and support during the implementation phase and create comprehensive documentation for AI models and systems.
• Vendor Management: Manage relationships with external vendors and service providers to ensure the best tools and services are utilized.
• Knowledge Sharing: Contribute to the development and maintenance of an internal knowledge base for AI use cases and communicate effectively with both technical and non-technical stakeholders.

Job Requirements:

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or a related field.
• 3+ years of experience in building and deploying AI models, with proven experience in Generative AI.
• Proficiency in AI frameworks such as TensorFlow, PyTorch, or Hugging Face Transformers.
• Experience with large language models, stable diffusion models, and other generative AI technologies.
• Experience with cloud platforms (e.g., AWS, Azure, GCP) and containerization tools like Docker and Kubernetes.
• Experience with CI/CD pipelines and version control systems like Git.
• Experience in scaling generative models and deploying them in production environments.
• Strong programming skills in Python, Java, and R.
• Understanding of machine learning algorithms, including supervised and unsupervised learning, reinforcement learning, and neural networks.
• Hands-on experience in maintaining infrastructure and optimizing AI models.

Interested parties please apply with full resume, state expected salaries by clicking "Apply". 

All applications and data collected will be treated in strict confidential and used exclusively for recruitment purposes. Only short listed candidates will be invited for interview. The company will retain the applications for a maximum period of 24 months and may refer suitable candidates to other vacancies within the Group.