Level AI
Lead Research Engineer - Applied AI
Level AI - San Francisco, California, United States, 94199
Work at Level AI
Overview
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Overview
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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
Qualifications
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
Why Join Us? Work at the frontier of LLM + agentic system research applied to real business problems.
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 Technology Industries Transportation, Logistics, Supply Chain and Storage Referrals increase your chances of interviewing at Level AI by 2x Sign in to set job alerts for “Research Engineer” roles.
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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
Qualifications
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
Why Join Us? Work at the frontier of LLM + agentic system research applied to real business problems.
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 Technology Industries Transportation, Logistics, Supply Chain and Storage Referrals increase your chances of interviewing at Level AI by 2x Sign in to set job alerts for “Research Engineer” roles.
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Palo Alto, CA $120,000.00-$160,000.00 2 weeks ago Research Scientist/Engineer, Mobile Manipulation - Behaviors
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Mountain View, CA $138,225.00-$207,575.00 1 week ago San Francisco, CA $100,000.00-$300,000.00 2 days ago Pleasanton, CA $85,000.00-$140,000.00 2 weeks ago Sunnyvale, CA $213,000.00-$293,000.00 1 week ago Perception Software or Machine Learning Engineer
Mountain View, CA $166,000.00-$244,000.00 1 week ago Research Engineer/Research Scientist, RL/Reasoning
Menlo Park, CA $180,000.00-$200,000.00 1 month ago Perception Engineer – ML/CV and Algorithms
San Jose, CA $130,000.00-$182,000.00 1 month ago Research Scientist / Engineer, World Modeling
Mountain View, CA $197,000.00-$291,000.00 2 weeks ago Research Scientist - Computational Chemistry
Oakland, CA $150,000.00-$200,000.00 2 weeks ago We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.
#J-18808-Ljbffr