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Lead AI - LLM Systems Engineer job at Snail Games USA in Los Angeles, CA

Snail Games USAvia Remote.co
RemotoLos Angeles, California, UsSêniorCLTOntem

Salário Estimado

R$ 11.880,00 - R$ 17.820,00

0de 100

Regular

Score da Vaga

Descrição da Vaga

Title: Lead AI / LLM Systems Engineer - Egofold Location: Culver City United States Job Description: About Snail Games USA Snail Games strives to create the new high bar for gameplay experience in online gaming.


We have been a global developer and publisher of digital entertainment since 2009 and are committed to pushing the boundaries of the industry.


About Egofold Egofold is an AI initiative within Snail Games focused on building a modular AI "brain" ecosystem for NPC intelligence, real-time perception systems, and simulation tooling across multiple game projects.


About the Role We are seeking a senior AI engineer to lead the development of Egofold's foundational AI systems.


This role is responsible for building and structuring a reusable, trainable LLM-based "brain" that can operate across multiple environments and contexts.


The focus is on core system design and execution: how the AI reasons, learns, adapts, and integrates training workflows over time.


This is a hands-on role for someone comfortable making technical decisions under ambiguity and operating without fully defined requirements.


Job Type Full-Time Location Hybrid - Los Angeles Area (3-4 in-office days per week) Responsibilities Design and implement foundational AI systems using large language models as a core reasoning component.


Architect simulation-based learning systems and training workflows, including fine-tuning, reinforcement learning, evaluation, and feedback loops.


Build validation, safety, and constraint layers around generative outputs to ensure predictable and controllable behavior.


Define evaluation frameworks and benchmarking strategies to measure agent performance, stability, and learning progression over time.


Structure how context, memory, and world state are represented and consumed within the AI architecture.


Determine how learned behavior, structured logic, and rule-based systems interact within a unified hybrid system.


Collaborate with engine engineers to integrate AI systems into real-time interactive environments.


Make system-level technical decisions that prioritize long-term reuse, scalability, and cross-domain adaptability.


Minimum Requirements Significant professional experience building AI or ML systems beyond simple model or API integration.


Demonstrated experience working with large language models in a production or applied research context.


Hands-on experience with agent training methodologies, including reinforcement learning or simulation-based learning systems.


Strong understanding of training workflows, evaluation strategies, and iterative improvement cycles.


Strong proficiency in Python and experience integrating AI systems into production environments.


Ability to reason about complex, stateful systems and learning behavior over time.


Comfort operating in early-stage, ambiguous environments and taking ownership of foundational systems.


Nice to Have Experience designing context-aware or agent-based AI systems.


Background in behavioral AI, simulation, or decision-making systems.


Familiarity with reinforcement learning, fine-tuning strategies, or hybrid AI architectures.


Experience integrating AI systems into real-time or interactive environments.


Familiarity with C++, C#, or Unreal Engine integration workflows.


Salary Range $150,000 - $200,000 Annually Why Join the Snail Games USA Team? Operate in a small, high-autonomy team with significant technical ownership and long-term influence.


True focus on work/life balance Paid company holidays, vacation, and separate sick leave Medical, dental, vision, and Life/LTD 401k with company match

Requisitos

  • Significant professional experience building AI or ML systems beyond simple model or API integration
  • Demonstrated experience working with large language models in a production or applied research context
  • Hands-on experience with agent training methodologies, including reinforcement learning or simulation-based learning systems
  • Strong understanding of training workflows, evaluation strategies, and iterative improvement cycles
  • Strong proficiency in Python and experience integrating AI systems into production environments
  • Ability to reason about complex, stateful systems and learning behavior over time
  • Comfort operating in early-stage, ambiguous environments and taking ownership of foundational systems
  • Experience designing context-aware or agent-based AI systems
  • Background in behavioral AI, simulation, or decision-making systems
  • Familiarity with reinforcement learning, fine-tuning strategies, or hybrid AI architectures
  • Experience integrating AI systems into real-time or interactive environments
  • Familiarity with C++, C#, or Unreal Engine integration workflows

Responsabilidades

  • This role is responsible for building and structuring a reusable, trainable LLM-based "brain" that can operate across multiple environments and contexts
  • The focus is on core system design and execution: how the AI reasons, learns, adapts, and integrates training workflows over time
  • Design and implement foundational AI systems using large language models as a core reasoning component
  • Architect simulation-based learning systems and training workflows, including fine-tuning, reinforcement learning, evaluation, and feedback loops
  • Build validation, safety, and constraint layers around generative outputs to ensure predictable and controllable behavior
  • Define evaluation frameworks and benchmarking strategies to measure agent performance, stability, and learning progression over time
  • Structure how context, memory, and world state are represented and consumed within the AI architecture
  • Determine how learned behavior, structured logic, and rule-based systems interact within a unified hybrid system
  • Collaborate with engine engineers to integrate AI systems into real-time interactive environments
  • Make system-level technical decisions that prioritize long-term reuse, scalability, and cross-domain adaptability

Benefícios

$150,000 - $200,000 Annually
True focus on work/life balance
Paid company holidays, vacation, and separate sick leave
Medical, dental, vision, and Life/LTD
401k with company match

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Informações

NívelSênior
ContratoCLT
LocalLos Angeles, California, Us
RemotoSim
MoedaBRL
PublicadaOntem
FonteRemote.co

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