Job Description
Are you ready to architect the intelligence of tomorrow? Aethelgard Innovations is seeking a visionary Senior Artificial Intelligence Engineer to lead the next generation of autonomous systems and generative models. As we look toward the technological landscape of 2026, we need a technical leader who thrives on solving complex, high-impact problems.
In this pivotal role, you will define the architecture for our proprietary LLMs, optimize model inference for edge devices, and spearhead our ethical AI initiatives. If you are passionate about the future of machine learning and want to build systems that define the era of 2026, we want to meet you.
Why Join Us?
- Work at the forefront of Generative AI and Autonomous Systems.
- Competitive compensation package including equity.
- Flexible remote-first policy with a vibrant SF office.
Responsibilities
- Model Architecture: Design, train, and deploy state-of-the-art Deep Learning models, specifically focusing on Transformers and Large Language Models (LLMs).
- System Optimization: Implement advanced MLOps pipelines to ensure scalability, low-latency inference, and high availability of AI services.
- Ethical AI Oversight: Establish and enforce governance frameworks for AI bias, safety, and transparency.
- R&D Leadership: Conduct cutting-edge research in Natural Language Processing (NLP) and Computer Vision to stay ahead of 2026 industry trends.
- Collaboration: Partner with product managers and data scientists to translate complex technical requirements into robust, production-ready solutions.
- Code Review: Mentor junior engineers and maintain high code quality standards across the AI engineering team.
Qualifications
- Education: Master’s or PhD in Computer Science, Mathematics, or a related field, with a focus on AI/ML.
- Technical Skills: Deep expertise in Python, PyTorch, TensorFlow, or JAX.
- Experience: 5+ years of professional experience in machine learning engineering or data science.
- Frameworks: Proven track record of deploying models at scale using Kubernetes, Docker, and cloud platforms (AWS/GCP/Azure).
- Programming: Strong proficiency in SQL and experience with vector databases (e.g., Pinecone, Milvus) for RAG applications.
- Soft Skills: Excellent communication skills with the ability to explain complex AI concepts to non-technical stakeholders.