Job Description
Architecting the Intelligence of Tomorrow
We are looking for a visionary Senior AI Engineer to join Aether Dynamics and help define the technology roadmap for the year 2026. In this pivotal role, you will be at the forefront of integrating next-generation generative models into scalable production environments.
Our mission is to bridge the gap between theoretical artificial intelligence and practical, high-impact applications. You will work alongside a world-class team of researchers and engineers to build autonomous agents and intelligent systems that redefine human-machine interaction.
Why Join Us?
- Work on cutting-edge AI infrastructure designed for the future.
- Competitive compensation and equity package.
- Flexible remote-first culture with a hub in San Francisco.
Responsibilities
- Design & Development: Spearhead the architecture and implementation of advanced Large Language Models (LLMs) and multimodal systems optimized for the 2026 technology stack.
- Performance Optimization: Engineer high-performance inference pipelines and optimize neural network architectures for low-latency, high-throughput environments.
- Research Integration: Translate cutting-edge research papers into production-ready code, integrating novel techniques such as Reinforcement Learning from Human Feedback (RLHF) and Chain-of-Thought reasoning.
- System Scalability: Build and maintain robust MLOps pipelines using Kubernetes and cloud-native services to ensure system reliability at scale.
- Cross-Functional Collaboration: Partner with product managers and designers to define AI features that drive user engagement and business growth.
Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related field; PhD preferred.
- Experience: 5+ years of professional experience in software engineering and machine learning, with a specific focus on NLP and Deep Learning.
- Technical Skills: Proficiency in Python, PyTorch, or TensorFlow; strong understanding of Transformer architectures and attention mechanisms.
- Problem Solving: Demonstrated ability to tackle complex algorithmic challenges and improve model accuracy and efficiency.
- Communication: Excellent verbal and written communication skills with the ability to articulate technical concepts to non-technical stakeholders.