About Level AILevel AI is revolutionizing customer experience by transforming contact centers into strategic assets through state-of-the-art AI. Our platform leverages LLMs and real-time intelligence to understand complex customer interactions and drive better business outcomes.
Role Overview - We’re looking for a hands-on and visionary Lead Applied AI Researcher to spearhead cutting-edge advancements in agentic AI systems. This role will focus on building intelligent, decision-making agents powered by reinforcement learning, LLM fine-tuning, and multi-agent frameworks to enhance our AI-native CX platform.
Key Responsibilities
- Design and build agentic systems that operate autonomously across multi-step tasks
- Apply and adapt reinforcement learning (RL) techniques to real-world interaction and decision-making problems
- Fine-tune and optimize large language models (LLMs) for dialog management, summarization, and real-time analysis of customer interactions
- Lead rapid prototyping and applied research on intelligent agent behavior, planning, and memory across various domains
- Collaborate closely with engineering, product, and data teams to bring research into production at scale
- Stay current with advancements in open-source LLMs, RL frameworks, and cognitive architectures, integrating them when relevant
- Publish internal whitepapers and influence long-term AI strategy at Level AI
- Experience in CS, Machine Learning, or a related field
- 5 - 10+ years in applied AI roles with proven contributions to LLM, RL, or agentic research
- Experience expertise in:
- Reinforcement Learning (e.g., PPO, GRPO)
- Agentic systems (planning, memory, autonomy)
- LLM fine-tuning (PEFT, LoRA, RLHF)
- Proficiency with PyTorch, Hugging Face, Ray RLlib, or similar libraries
- Experience shipping research to production in high-stakes environments
- Strong publication record or open-source contributions a plus
- BonusExperience with dialog agents, retrieval-augmented generation (RAG), or multi-agent collaboration frameworks
- Background in building or scaling tool-using agents in enterprise contexts
Collaborate with a world-class team in a high-growth, Series C startup.
Competitive salary, equity, and benefits.
Seniority level
Seniority level
Mid-Senior level
Employment type
Employment type
Full-time
Job function
Job function
Engineering and Information TechnologyIndustries
Transportation, Logistics, Supply Chain and Storage
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