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Salary: USD 195,000 - 204,750 / annual
Archer Technologies, headquartered in Silicon Valley, is a leader in next-generation aerospace building an end-to-end advanced air mobility platform that delivers air taxis, unmanned aircraft systems (UAS), and aviation-related AI solutions to customers across commercial aerospace and defense sectors.
You will design, implement, and evaluate novel machine learning and deep learning algorithms with a specific focus on autonomy, trajectory prediction, and perception. Your work will span the full research lifecycle: starting from identifying the data needed for training, designing model architectures and input/output representations, conducting rigorous evaluation, and ultimately assisting in transitioning research prototypes into production-ready systems.
Key responsibilities include:
- Iterating on predictive and decision-making model development
- Collaborating with other research engineers to prototype and validate complex solutions from academic literature related to agent behavior and environmental understanding
- Conducting experiments to benchmark new techniques and evaluate model behavior in dynamic or simulated environments
- Developing tools and frameworks to support scalable and reproducible research
- Communicating research findings to leadership in a concise and convincing manner
- Staying current with the latest developments in autonomy and generative AI to identify relevant innovations
This is a hands-on technical role where you will drive innovation in AI/ML for aerospace applications, working at the intersection of cutting-edge research and real-world deployment challenges.
**Requirements:**
- Master's Degree in Artificial Intelligence, Computer Science, Computer or Electrical Engineering, Computational Sciences, Machine Learning, Robotics, or Informatics
- Highly skilled with AI/ML frameworks such as PyTorch or TensorFlow
- Strong skills in debugging and determining requirements for AI models in terms of data, training, and evaluation
- Understanding of Transformer architectures, attention mechanisms, multi-modal foundation models, diffusion policies, fine-tuning, model distillation, and mixture of experts
- Job code SJ2026NZ must be included on resume/CV and cover letter
