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AAutofleet
Tel Aviv, Israel2 months ago
Grade
Middle
Experience
from 3 years
English level
B2, upper-intermediate
An email or a Telegram message to the recruiter
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.
Enterprise AI Agent Development: Designing, building, and deploying AI agents that automate and augment high-value workflows across business functions Agentic Architecture & Orchestration: Owning the end-to-end agent stack - from tool use, memory management, and multi-step planning to human-in-the-loop escalation patterns, guardrails and audit trails. Evaluation & Continuous Improvement: Defining agent evaluation frameworks that measure task completion, accuracy, hallucination rates, latency, and business impact - then iterating on agent behavior based on real usage data and stakeholder feedback. Collaborate with engineering teams to design, build, and maintain production pipelines. 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.
Master’s/Ph.D. in Computer Science, Electrical Engineering, Machine Learning, information systems engineering, or related field. 3+ years of applied AI/ML experience with a focus on Generative AI, LLMs, and deep learning. Depth in agentic system design, retrieval-augmented generation, context and tool engineering, and rigorous evaluation. Familiarity with AI frameworks (e.g., HuggingFace Transformers, LangChain, scikit-learn, PyTorch) Familiarity with embedding models and vector databases Exceptional problem-solving, creative thinking, and analytical skills. Experience with voice AI technologies, speech recognition, or text-to-speech systems - strong advantage.
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 Enterprise AI Agent Development: Designing, building, and deploying AI agents that automate and augment high-value workflows across business functions Agentic Architecture & Orchestration: Owning the end-to-end agent stack - from tool use, memory management, and multi-step planning to human-in-the-loop escalation patterns, guardrails and audit trails. Evaluation & Continuous Improvement: Defining agent evaluation frameworks that measure task completion, accuracy, hallucination rates, latency, and business impact - then iterating on agent behavior based on real usage data and stakeholder feedback. Collaborate with engineering teams to design, build, and maintain production pipelines. 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. 3+ years of applied AI/ML experience with a focus on Generative AI, LLMs, and deep learning. Depth in agentic system design, retrieval-augmented generation, context and tool engineering, and rigorous evaluation. Familiarity with AI frameworks (e.g., HuggingFace Transformers, LangChain, scikit-learn, PyTorch) Familiarity with embedding models and vector databases Exceptional problem-solving, creative thinking, and analytical skills. Experience with voice AI technologies, speech recognition, or text-to-speech systems - strong advantage.
We compare skills, grade, work format and salary
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