DevJobs

AI Applied Researcher

Overview
Skills
  • Python Python
  • Evaluation methodologies of LLMs
  • Fine-tuning techniques
  • Generative AI models
  • Hugging Face
  • LangChain
  • LlamaIndex
  • Multi-agents
  • Prompt engineering
  • RAG architectures
  • Transformers
  • Data exploration
  • Data visualization
  • Embedding models
  • Vector databases
We are making the future of Mobility come to life starting today.

At Autofleet we support the world's largest vehicle fleet operators and transportation providers to optimize existing operations and seamlessly launch new, dynamic business models - driving efficient operations and maximizing utilization.

We are looking for a talented AI Applied Researcher to help us develop advanced AI solutions that will empower impactful projects. The Data Science team leads the AI research and innovation efforts of the company, and is focused on pushing AI boundaries to enhance the product and optimize processes.

What You'll Do

  • Lead an applied research for AI-driven features in the Autofleet platform
  • Research and optimization agentic flows to solve complex problems
  • Collaborate with engineering teams to design, build, and maintain production pipelines
  • Conduct experiments and evaluate the performance of AI models, algorithms, and techniques
  • Stay up to date with the latest developments in AI, machine learning, and related fields, focusing on LLMs, exploring how emerging technologies can be applied to improve products and services.


Requirements

  • Master's/Ph.D. in Computer Science, Electrical Engineering, Machine Learning, information systems engineering, or related field
  • 5+ years of hands-on experience with developing & maintaining production class Machine Learning projects aimed towards solving business problems
  • High proficiency in Python
  • Hands-on proficiency with modern generative AI models, prompt engineering, multi-agents, and RAG architectures. Also, a solid understanding of transformers, optimized fine-tuning techniques, and evaluation methodologies of LLMs while using relevant frameworks (Hugging Face, LangChain, LlamaIndex, etc)
  • Familiarity with embedding models and vector databases - advantage
  • Experience in data exploration and visualization
AutoFleet