Job Description
Join Nexus Future Labs as we define the technological landscape for the year 2026. We are not just building software; we are architecting the future of autonomous systems and quantum-enhanced computing. If you are a visionary engineer with a passion for pushing the boundaries of what's possible, this is your opportunity to lead a world-class team in a high-growth environment.
We are looking for a Lead AI Architect to spearhead our research and development initiatives. You will bridge the gap between theoretical AI models and scalable, production-grade infrastructure. This role requires a deep understanding of next-gen neural architectures and a knack for solving complex, large-scale problems.
Why Join Us?
- Work on cutting-edge AI technologies with a direct impact on the 2026 roadmap.
- Competitive compensation package including equity and performance bonuses.
- Flexible remote-first policy with access to state-of-the-art San Francisco facilities.
- Opportunity to mentor junior developers and shape the culture of innovation.
Responsibilities
- Architect and implement scalable AI/ML infrastructure capable of handling exabyte-scale data processing.
- Lead the technical vision for the 2026 product suite, focusing on Generative AI and predictive analytics.
- Collaborate with cross-functional teams (Data Science, Product, Engineering) to define technical requirements and roadmaps.
- Optimize existing models for speed, accuracy, and resource efficiency.
- Establish best practices for code quality, testing, and deployment pipelines.
- Conduct research into emerging AI paradigms to keep the organization at the forefront of innovation.
Qualifications
- 10+ years of experience in software engineering, with at least 5 years in AI/ML architecture.
- Advanced degree (Master's or PhD) in Computer Science, Mathematics, or a related field.
- Deep expertise in Python, TensorFlow, PyTorch, and distributed computing frameworks.
- Proven track record of deploying large-scale machine learning models into production environments.
- Strong understanding of cloud platforms (AWS, GCP, or Azure) and containerization technologies (Kubernetes, Docker).
- Excellent communication skills with the ability to articulate complex technical concepts to non-technical stakeholders.