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We are seeking an Agent Systems Engineer who can operate with a high degree of autonomy in an early-stage, fast-moving environment. This role is suitable for a recent graduate or early-career engineer with strong AI fundamentals who is capable of taking ownership of meaningful systems and helping shape technical direction. You will work on agent behavior, learning systems, and simulation infrastructure, and may be asked to drive initiatives end-to-end rather than executing narrowly defined tasks.
Job Responsibility:
Design, implement, and iterate on agent behavior systems within simulated or virtual environments
Build and evolve training, evaluation, and experimentation pipelines for adaptive agents
Explore and compare different approaches to decision-making, learning, and control
Take ownership of technical problems where solutions are not predefined
Collaborate closely with a small, senior team to shape architecture and technical direction
Support internal reviews and external demonstrations through clear validation of agent behavior and progress
Requirements:
Strong academic or practical background in artificial intelligence, machine learning, or related fields
Demonstrated familiarity with AI concepts such as reinforcement learning, agent-based systems, or learning-driven decision-making
Strong programming skills in one or more relevant languages (e.g., Python, C++)
Ability to reason about complex systems, state, feedback loops, and emergent behavior
Comfort working in ambiguous, startup-like environments with evolving goals and constraints
Clear communication skills and willingness to challenge assumptions
Nice to have:
Hands-on experience with reinforcement learning frameworks or simulation environments
Background in game AI, robotics, or embodied AI research
Experience building prototypes, research projects, or experimental systems independently
Familiarity with game engines or custom simulation tooling
What we offer:
Opportunity to be a driving force on foundational systems at an early stage
Startup-like ownership with real technical impact
Exposure to applied AI problems beyond narrow academic exercises
True focus on work/life balance
Paid company holidays, vacation, and separate sick leave