Job Description
Are you ready to architect the future of autonomous intelligence? Nexus Horizon Labs is seeking a visionary Lead Synthetic Intelligence Architect 2026 to spearhead our next-generation research initiatives.
We are on the bleeding edge of synthetic intelligence, building systems that mimic and exceed human cognitive capabilities. As a key member of our elite R&D division, you will define the architectural blueprints for the AI models that will power industries in the mid-2020s and beyond.
Why Join Us?
- Impact: Shape the core algorithms that define the future of automation.
- Equity: Competitive equity package for long-term ownership.
- Environment: Work with a world-class team of neuroscientists and computer engineers.
We are looking for a strategic thinker who is equally comfortable diving into code as they are in presenting high-level roadmaps to stakeholders.
Responsibilities
- Design and implement scalable, high-performance neural architectures for next-gen synthetic intelligence models.
- Lead the end-to-end machine learning lifecycle, from data ingestion and preprocessing to model training and deployment.
- Establish best practices for MLOps, ensuring reproducibility, monitoring, and automated scaling of AI systems.
- Mentor and guide a team of junior data scientists and ML engineers, fostering a culture of innovation and technical excellence.
- Collaborate with cross-functional teams (Product, Security, Legal) to ensure AI systems are robust, ethical, and compliant with global standards.
- Conduct cutting-edge research to stay ahead of industry trends and integrate emerging technologies into our core stack.
Qualifications
- Ph.D. or Master’s degree in Computer Science, Mathematics, or a related field with a focus on Artificial Intelligence.
- 8+ years of professional experience in software engineering and machine learning, with at least 3 years in a leadership or architect role.
- Deep expertise in deep learning frameworks such as PyTorch, TensorFlow, or JAX.
- Strong proficiency in programming languages including Python, C++, and CUDA.
- Proven track record of deploying large-scale machine learning models to production environments.
- Experience with natural language processing (NLP) and/or computer vision is highly preferred.