Software Developer, Generative AI
GeotabAbout the role
Who we are:
Geotab ® is a global leader in IoT and connected transportation and certified “Great Place to Work™.” We are a company of diverse and talented individuals who work together to help businesses grow and succeed, and increase the safety and sustainability of our communities. Geotab is advancing security, connecting commercial vehicles to the internet and providing web-based analytics to help customers better manage their fleets. Geotab’s open platform and Geotab Marketplace ®, offering hundreds of third-party solution options, allows both small and large businesses to automate operations by integrating vehicle data with their other data assets. Processing billions of data points a day, Geotab leverages data analytics and machine learning to improve productivity, optimize fleets through the reduction of fuel consumption, enhance driver safety and achieve strong compliance to regulatory changes. Our team is growing and we’re looking for people who follow their passion, think differently and want to make an impact. Ours is a fast paced, ever changing environment. Geotabbers accept that challenge and are willing to take on new tasks and activities - ones that may not always be described in the initial job description. Join us for a fulfilling career with opportunities to innovate, great benefits, and our fun and inclusive work culture. Reach your full potential with Geotab. To see what it’s like to be a Geotabber, check out our blog and follow us @InsideGeotab on Instagram. Join our talent network to learn more about job opportunities and company news.Who you are:
We are always looking for amazing talent who can contribute to our growth and deliver results! Geotab is seeking a Software Developer who will be instrumental in the development and integration of state-of-the-art generative AI capabilities, with a particular focus on Large Language Models (LLMs), into Geotab’s product offerings. This role involves designing and deploying AI-driven applications, enriching products and services with intelligent generative features, and upholding the entire lifecycle of generative AI solutions. If you love technology, and are keen to join an industry leader — we would love to hear from you!
What you'll do:
As a Software Developer for our Generative AI team, your key area of responsibility will be designing and deploying applications that harness the power of Large Language Models to provide innovative solutions, while optimizing and customizing LLM applications according to specific case requirements to ensure efficiency and scalability. You will need to work closely with cross-functional teams and data scientists to seamlessly integrate LLMs within various enterprise products and services and gather requirements for data science workflows.
To be successful in this role you will be a strong team player with an entrepreneurial mindset and the aptitude to simplify complex AI concepts and data insights for stakeholders not specialized in ML/AI. In addition, the successful candidate will have strong analytical and problem-solving skills with the ability to manage multiple tasks and projects simultaneously while navigating the inherent uncertainties of a research environment.
How you'll make an impact:
- Design and deploy applications that harness the power of Large Language Models to provide innovative solutions.
- Collaborate with cross-functional teams to seamlessly integrate LLMs within various enterprise products and services.
- Optimize and customize LLM applications according to specific case requirements, prioritizing efficiency and scalability.
- Remain updated on cutting-edge advancements in AI/ML in areas related to LLMs, Agents, retrieval augmented generation (RAG), and Generative AI.
- Lead the full product lifecycle from initial ideation to deployment and ongoing maintenance.
- Develop methodology for LangChain utilization and engage with vector databases to enhance Generative AI applications.
- Apply LLM expertise in a product-focused manner, sharing passion through professional or personal project involvement.
- Navigate the research environment's inherent uncertainties with ease.
- Resolve complex technical challenges
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