Geotab is looking to integrate state-of-the-art generative AI capabilities, specifically Large Language Models (LLMs), into its product offerings to enhance its connected transportation solutions.
Requirements
- Proficiency in Python programming with 3+ years of hands-on experience, coupled with best practice knowledge
- Experience in working with LangChain, Semantic Kernel, or AutoGen to construct scalable Generative AI applications strongly preferred
- Familiarity with vector databases and their practical implementation and optimization techniques
- Experience building RAG (Retrieval Augmented Generation) applications is a plus
- Solid understanding of LLMs, including prompt engineering, fine-tuning, LLMOps, function-calling, and retrieval augmented generation
- Experience working with server side frameworks like FastAPI as well as API development, documentation, and versioning
- Experience with API design and implementation
Responsibilities
- Designing and deploying AI-driven applications
- Enriching products and services with intelligent generative features
- Upholding the entire lifecycle of generative AI solutions
- Weaving LLMs into diverse products and services
- Providing technical leadership and stewardship throughout all phases of the product life cycle
- Optimize and customize LLM applications according to specific case requirements, prioritizing efficiency and scalability
- Develop methodology for LangChain utilization and engage with vector databases to enhance Generative AI applications
Other
- Post-secondary Degree specialization in Computer Science, Software or Computer Engineering or a related field.
- 1-5 years of experience in software development with experience working on AI/ML/LLM applications.
- Commercial software engineering experience with a strong foundation in coding and a keen interest in Generative AI.
- Ability to leverage Generative AI knowledge in a product-centric manner.
- Proven experience dealing with ambiguous problems typically found in a research environment.
