Key Responsibilities:
- Develop efficient, maintainable code while adhering to best practices in software engineering.
- Utilize DevSecOps tools for code deployment and version control.
- Conduct in-depth research and analysis on retrieval techniques, language models, and generative AI methods.
- Collaborate with data engineers to ensure the efficiency and accuracy of data pipelines.
- Continuously refine Retrieval Augmented Generation (RAG) methods, including embedding, chunking, and search algorithm optimization through experimentation and feedback.
- Explore various retrieval strategies, such as information retrieval, nearest-neighbor searches, or knowledge graph-based approaches, to enhance generative AI models.
- Optimize and fine-tune AI models for improved performance, scalability, and accuracy.
- Partner with cross-functional teams, including product managers, data scientists, and engineers, to understand requirements and deliver AI-driven solutions.
- Present insights and findings to stakeholders, contributing to strategic decisions.
- Document AI models, algorithms, and processes thoroughly.
- Prepare technical reports and presentations to effectively communicate results.
- Stay current with the latest advancements in AI and machine learning technologies.
- Participate in Agile ceremonies to execute prioritized projects and features.
- Implement automated testing and monitoring to ensure AI system accuracy and reliability.
Education:
- Qualifications are evaluated on a case-by-case basis, but preferred backgrounds include fields such as Mathematics, Statistics, Computer Science, Data Science, Analytics, Physics, or Bioinformatics.
Requirements:
- 4+ years of experience in AI engineering.
- Proficiency in Python programming.
- Experience in building scalable AI solutions using modern technology stacks, including cloud services, data pipelines, databases, and necessary tooling.
- Familiarity with CI/CD processes and test-driven development.
- Experience in developing Restful APIs for AI models.
- Strong understanding of machine learning concepts, including neural networks, optimization algorithms, and evaluation metrics.
- Knowledge of Retrieval Augmented Generation (RAG) techniques.
- Familiarity with prompt engineering techniques like instruction design, template-based approaches, rule-based conditioning, or fine-tuning strategies.
- Excellent communication and collaboration skills.
- Strong analytical and organizational skills, capable of managing multiple projects.
Preferred:
- Experience with Agile methodologies.
- Knowledge of additional programming languages such as Node.js, TypeScript, C#, or Java.
- Demonstrated experience in developing and refining prompts for generative AI models, particularly in creative or text generation areas.
- Experience with AWS Cloud and building, deploying, and managing Docker images.
Interested candidates who wish to apply for the advertised position, please clock on Apply. We regret that only shortlisted candidates will be notified.
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