Job Description
We are rewriting the rules of artificial intelligence. At Aether Dynamics, we are building the core intelligence systems for our flagship Project 2026 initiative—a next-generation autonomous infrastructure platform. We are seeking a visionary Senior AI Engineer to lead the development of our neural architectures and drive the future of cognitive computing.
In this role, you won't just be maintaining legacy systems; you will be architecting the brain of tomorrow. You will work with a world-class team of researchers and hardware engineers to deploy state-of-the-art models that operate at the edge and scale in the cloud. If you are passionate about pushing the boundaries of what is possible in AI and want to be part of the vanguard of technological evolution, we want to meet you.
Why Join Us?
- Work on a product that defines the future of urban mobility.
- Competitive equity and top-tier compensation package.
- Flexible remote-first policy with access to world-class amenities.
- Continuous learning budget and access to cutting-edge research labs.
Responsibilities
- Architect Neural Architectures: Design and implement scalable deep learning models tailored for low-latency inference in resource-constrained environments.
- Model Optimization: Collaborate with MLOps teams to optimize model performance, reduce latency, and improve accuracy using techniques like quantization and pruning.
- Research & Development: Stay at the forefront of AI research, exploring novel approaches in reinforcement learning and multimodal perception.
- Code Leadership: Mentor junior engineers, conduct rigorous code reviews, and establish best practices for reproducibility and testing within the project.
- Deployment: Oversee the end-to-end deployment of AI models to production pipelines, ensuring robustness and monitoring model drift.
Qualifications
- Education: Master’s or Ph.D. in Computer Science, Robotics, Mathematics, or a related field with a focus on Artificial Intelligence.
- Experience: Minimum of 5 years of professional experience in developing and deploying production-level AI/ML systems.
- Core Tech Stack: Proficiency in Python, PyTorch, or TensorFlow, with a deep understanding of GPU acceleration (CUDA).
- System Design: Strong understanding of distributed systems, cloud infrastructure (AWS/GCP), and containerization technologies (Docker/Kubernetes).
- Problem Solving: Demonstrated ability to tackle complex, unstructured problems and derive innovative solutions.
- Communication: Excellent written and verbal communication skills, with the ability to translate technical concepts for cross-functional teams.