Job Description
We are at the precipice of a technological paradigm shift, and the year 2026 represents the inflection point for autonomous AI systems. Nexus Future Systems is seeking a visionary Lead AI Architect to spearhead our next-generation predictive modeling and generative intelligence initiatives.
In this pivotal role, you won't just be maintaining legacy systems; you will be architecting the infrastructure that powers our operations well into the next decade. We are looking for a technical leader who thrives in ambiguity and possesses the foresight to design scalable, ethical, and groundbreaking AI solutions.
Join a diverse team of world-class engineers, data scientists, and strategists in the heart of San Francisco's tech district. You will have the autonomy to push the boundaries of what is possible, directly influencing our 2026 roadmap and beyond.
Why Join Us?
- Work on cutting-edge AI technologies that define the future.
- Competitive equity package and comprehensive benefits.
- Flexible remote-first hybrid work environment.
- Access to state-of-the-art computing infrastructure.
Responsibilities
- Architect Future-Proof Systems: Design and implement scalable machine learning pipelines and neural network architectures specifically optimized for the demands of 2026 and beyond.
- Strategic Roadmapping: Define the technical vision for our AI roadmap, identifying emerging technologies (e.g., AGI, quantum-ready algorithms) that provide a competitive edge.
- Team Leadership & Mentorship: Lead a high-performing team of data scientists and ML engineers, fostering a culture of innovation, continuous learning, and technical excellence.
- Model Optimization: Oversee the training, fine-tuning, and deployment of large language models (LLMs) and computer vision systems to ensure peak performance and low latency.
- Ethical AI Compliance: Ensure all AI systems adhere to strict ethical guidelines, bias mitigation protocols, and regulatory compliance standards.
- Cross-Functional Collaboration: Partner with product managers, engineering leads, and stakeholders to translate complex business requirements into robust technical solutions.
- Performance Analysis: Continuously monitor system performance, troubleshoot complex bottlenecks, and implement architectural improvements to handle massive data throughput.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field from a top-tier institution.
- Experience: Minimum of 8+ years of experience in software engineering and 5+ years of specialized experience in designing and deploying AI/ML systems.
- Technical Proficiency: Deep expertise in Python, TensorFlow, PyTorch, or JAX. Experience with distributed computing systems (Kubernetes, Apache Spark) is highly preferred.
- Strategic Vision: Proven track record of leading technical strategy and executing long-term roadmaps in a fast-paced, startup environment.
- Communication: Exceptional ability to communicate complex technical concepts to non-technical stakeholders and executive leadership.
- Problem Solving: Demonstrated ability to tackle ambiguous problems and deliver innovative solutions under tight deadlines.
- Certifications: AWS Certified Machine Learning Specialty or Google Professional Machine Learning Engineer certification is a plus.