AI Applied Researcher
At a glance
Mid-level AI Research role at Autofleet. Tel Aviv-Yafo.
Pay not stated AI Research salary
aimlroles summary, based on the employer's posting.
What you'll do
- Build and launch AI agents that handle or support important workflows across business teams
- Shape the agent system, including tools, memory, planning, human escalation, safeguards and audit records
- Create ways to score agents on task success, accuracy, hallucinations, speed and business results, then refine them using real usage
- Work with engineering to build and maintain production pipelines
- Track new AI and machine-learning developments, especially in LLMs, and assess product applications
What you bring
- A master’s or doctorate in computer science, electrical engineering, machine learning, information systems engineering or a related discipline
- At least three years applying AI or machine learning, with work centered on generative AI, LLMs and deep learning
- Strong grounding in agent design, retrieval-augmented generation, context and tool engineering, and careful evaluation
Who this fits
This mid-level role suits someone with applied AI experience who can take agent systems from design through production and ongoing evaluation. The job is onsite in Tel Aviv-Yafo, Israel.
From the employer
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.