Job Description
Are you ready to architect the future of intelligence? Quantum Horizon Technologies is seeking a visionary Senior AI Architect to spearhead our cutting-edge research and development for the 2026 roadmap. We are building the infrastructure that will define the next generation of autonomous systems and generative AI.
In this role, you will not just write code; you will design the very fabric of our AI ecosystem. You will bridge the gap between theoretical machine learning research and scalable production systems. If you are passionate about pushing the boundaries of what is possible in Artificial General Intelligence (AGI) and want to leave a lasting legacy in the tech industry, we want to meet you.
Why join us?
- Work on high-impact projects that shape the future of technology.
- Competitive compensation and equity packages.
- Flexible work environment in the heart of Seattle.
Key Objectives:
- Lead the architectural design for our next-generation LLMs and neural networks.
- Define the technical strategy for the 2026 product line.
- Ensure system scalability, security, and ethical AI compliance.
Responsibilities
- Design and implement scalable, robust Neural Network architectures for large-scale language models and computer vision systems.
- Lead a cross-functional team of data scientists and ML engineers to deliver high-performance AI solutions.
- Collaborate with product managers to translate complex AI capabilities into user-centric features.
- Establish best practices for MLOps, data pipeline management, and model deployment.
- Conduct rigorous code reviews and architectural planning sessions.
- Stay ahead of industry trends in AI research to ensure our roadmap remains competitive.
Qualifications
- Master’s or Ph.D. in Computer Science, Machine Learning, or a related technical field.
- Minimum of 7+ years of experience in software engineering, with at least 4 years specifically focused on AI/ML architecture.
- Expert proficiency in Python, PyTorch, or TensorFlow.
- Deep understanding of distributed systems, cloud architecture (AWS/Azure/GCP), and containerization (Docker/Kubernetes).
- Proven track record of deploying production-grade AI models.
- Strong communication skills with the ability to explain complex technical concepts to non-technical stakeholders.