5 months ago
Dallas, TX, USAStaff+
Responsibilities
- Own the architecture, training, fine-tuning, optimization, and deployment of agentic AI models.
- Develop autonomous behaviors using reinforcement learning, adaptive algorithms, retrieval-augmented generation, persistent memory, and multi-agent collaboration.
- Collaborate with hardware, software, and product teams to integrate AI models into autonomous and embedded systems.
- Prototype and iterate on multi-agent and reinforcement-learning approaches for real-world, resource-constrained environments.
- Optimize models for speed, reliability, efficiency, and integration with embedded hardware.
- Identify applications for agentic models across edge and embedded AI systems.
Requirements
- Demonstrated hands-on experience developing AI models for agentic systems through innovative real-world projects or technical publications.
- Experience with autonomous agent modeling, reinforcement learning, adaptive algorithms, retrieval-augmented generation, persistent memory, and multi-agent collaboration.
- Fluency in Python and C/C++.
- Experience with TensorFlow, PyTorch, or similar AI platforms.
- Strong problem-solving, communication, and cross-functional collaboration skills.
Benefits
- Work on advanced AI innovation for intelligent embedded systems in automotive, industrial automation, and IoT applications.
- Collaborate with experienced engineers and work across the full software and hardware stack.
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