Job Description
Are you ready to architect the future of artificial intelligence?
Aethelgard Systems is on the cutting edge of the 2026 technological landscape, developing next-generation neural networks that will redefine human-machine interaction. We are seeking a visionary Senior AI/ML Architect to lead our advanced R&D division. If you are passionate about pushing the boundaries of Deep Learning, Large Language Models (LLMs), and Quantum-ready algorithms, this is your opportunity to shape the future.
Why Join Us?
- Impact: Work on projects that will power the autonomous systems of tomorrow.
- Culture: A forward-thinking, remote-first culture with a focus on cognitive diversity and innovation.
- Growth: Competitive equity packages and continuous learning opportunities in emerging tech stacks.
Join us in building the intelligence layer of the digital world.
Responsibilities
- Design, implement, and deploy scalable machine learning pipelines and neural network architectures optimized for future hardware (e.g., neuromorphic chips).
- Lead the research and development of proprietary Large Language Models (LLMs) and generative AI agents.
- Optimize model inference latency and accuracy, ensuring systems are robust against adversarial attacks and data drift.
- Collaborate with cross-functional teams including data engineers, product managers, and security experts to integrate AI solutions into production environments.
- Mentor junior engineers and data scientists, fostering a culture of technical excellence and innovation.
- Stay abreast of the latest breakthroughs in AI research and proactively integrate them into our product roadmap.
Qualifications
- Master’s or PhD in Computer Science, Mathematics, or a related field, with a focus on Artificial Intelligence, Deep Learning, or Machine Learning.
- Proven experience (5+ years) designing and deploying production-grade AI models, specifically in Python and C++.
- Deep expertise in Deep Learning frameworks such as PyTorch, TensorFlow, or JAX.
- Strong understanding of distributed systems, cloud infrastructure (AWS/GCP/Azure), and containerization technologies (Docker/Kubernetes).
- Experience with MLOps tools, model versioning, and data orchestration platforms.
- Excellent problem-solving skills and the ability to communicate complex technical concepts to non-technical stakeholders.