Lead Research Engineer, Level AI

Applied Artificial Intelligence

Salary not provided

+ Equity

PyTorch

Senior and Expert level

San Francisco Bay Area

AI & natural language understanding (NLU) for call centers

Open for applications

AI & natural language understanding (NLU) for call centers

101-200 employees

B2BArtificial IntelligenceEnterpriseAnalyticsCustomer serviceSaaSAutomation

Open for applications

Salary not provided

+ Equity

PyTorch

Senior and Expert level

San Francisco Bay Area

101-200 employees

B2BArtificial IntelligenceEnterpriseAnalyticsCustomer serviceSaaSAutomation

Company mission

To blend human and machine intelligence to transform customer experiences.

Job

Company

Role

Who you are

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

What the job involves

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
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

Our take

Contact centres are vital for businesses, but they face challenges like high turnover, low efficiency, and managing large volumes of customer interactions,. Traditional methods often fall short in improving service quality and securely handling customer data.

Level AI addresses these challenges with AI-powered tools that enhance contact centre operations. Using generative AI and large language models (LLMs), the platform analyzes customer conversations, provides real-time agent support, and automates tasks like quality assurance and sentiment analysis.

Having recently landed significant funding, the company is ready to expand its team and further innovate. With these resources, level AI is set to make even bigger waves in the contact centre world, helping businesses improve customer interactions and boost efficiency.

Kirsty

Company Specialist at Welcome to the Jungle

Insights

Top investors

Glassdoor (4.2)

Company

Funding (last 2 of 4 rounds)

Jul 2024

$39.4m

SERIES C

Mar 2022

$20m

EARLY VC

Total funding: $74.4m

Company benefits

Equity
Unlimited paid vacation
Remote work options

Company HQ

Old Mountain View, Mountain View, CA

Leadership

Ashish Nagar

(CEO)

Previously a Product Manager at Amazon Alexa's Conversational AI Team. Worked as Director of Product & Business at both Relcy, Inc. and Kinestral Technologies Inc. Also worked as a Venture Capitalist at Investor Growth Capital and was a Senior Associate at The Boston Consulting Group.

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