Note: The job is a remote job and is open to candidates in USA. Future of Life Institute (FLI) is seeking a Research Engineer to develop novel AI platforms that address critical alignment challenges and practical LLM agents. The role involves combining platform development with alignment research, requiring expertise in agent-based systems and multi-objective optimization to create systems that support safety research and implement cooperative AI architectures.
Responsibilities
- Research and develop AI systems and platforms variously for: safety research, internal tooling, and safety community support
- Design and implement architectures for agent execution environments and interaction platforms
- Develop optimization algorithms for multi-objective and cooperative AI systems
- Create mechanisms for conflict resolution and preference aggregation in multi-agent settings
- Implement testing frameworks and example environments to validate theoretical approaches
- Build middleware components that facilitate secure and efficient agent communication
- Architect and develop reusable software components for AI alignment research
- Document system architectures, APIs, and implementation details
- Collaborate on technical publications and research presentations
- Contribute to both practical implementations and theoretical research in AI alignment
- Support the evaluation and refinement of research prototypes
Skills
- MS or PhD in Computer Science, AI, or related field (or equivalent experience)
- Experience with one or preferrably more of: dynamic plan recognition, activity recognition, dynamic multicriteria decision making, multi-agent systems, or AI builder platforms
- Strong programming skills in both Python and Java
- Demonstrated ability to relatively independently drive technical projects from concept to implementation
- Familiarity with techniques for AI alignment, control, safety, or related research areas
- Experience developing middleware, frameworks, or platforms
- Breadth of experience in machine learning and AI systems architecture
- Literate in semi-formal semantics
- Excellent communication skills and technical documentation abilities
- Publications (formal or informal) in AI alignment, AI safety, or related research areas
- Familiarity with varied multi-objective optimization techniques
- Experience with contextual pragmatics and/or constraint satisfaction problems
- Developed novel multi-agent architectures
- Experience with LLMs and integrating them into agent architectures
- Experience with distributed systems and platform development
- Knowledge of security and privacy methods for multi-party computation
- Understanding of basic game theory and/or social choice theory concepts
- Familiarity with metacognitive systems, metareasoning, or dynamical cognitive approaches
- Demonstrable open source project contributions
- Experience building systems that actively manage trade-offs between competing objectives
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