Job Description
The Opportunity:
Nexus Future Systems is on a mission to redefine the technological landscape of the next decade. We are seeking a visionary Senior AI Architect to lead the core development of Project 2026, our upcoming breakthrough in generative artificial intelligence and autonomous decision-making systems.
In this role, you won't just be writing code; you will be architecting the future. You will work with a world-class team of engineers, data scientists, and strategists to build scalable, ethical, and robust AI models that will power the next generation of enterprise solutions.
Why Join Us?
- Work on cutting-edge technology that defines the year 2026 and beyond.
- Competitive equity package and performance bonuses.
- Flexible remote-first culture with a hub in the heart of San Francisco.
What You'll Do:
We are looking for a technical leader who can bridge the gap between theoretical research and production-grade engineering. You will be responsible for the end-to-end lifecycle of our AI infrastructure.
Responsibilities
- Design & Architect: Lead the architectural design of scalable machine learning pipelines and neural network architectures for Project 2026.
- Model Optimization: Engineer high-performance models that operate efficiently in real-time environments with low latency.
- Technical Leadership: Mentor a team of junior engineers and data scientists, conducting code reviews and establishing best practices for AI development.
- Deployment: Oversee the CI/CD pipelines, containerization (Docker/Kubernetes), and cloud infrastructure (AWS/Azure) for model deployment.
- Innovation: Stay at the forefront of AI research, identifying new methodologies to improve model accuracy and reduce bias.
- Collaboration: Partner with product managers and stakeholders to translate complex technical requirements into feasible engineering solutions.
Qualifications
- Experience: 7+ years of professional experience in software engineering, with a minimum of 4 years specifically in Artificial Intelligence and Machine Learning.
- Technical Stack: Proficiency in Python, PyTorch, TensorFlow, or JAX. Experience with distributed computing frameworks (Spark, Ray) is highly desirable.
- Infrastructure: Strong understanding of cloud platforms (AWS, GCP), containerization (Docker), and orchestration (Kubernetes).
- Education: BS, MS, or PhD in Computer Science, Statistics, Mathematics, or a related technical field.
- Soft Skills: Exceptional problem-solving abilities and the ability to communicate complex technical concepts to non-technical stakeholders.
- Leadership: Proven track record of leading engineering teams and delivering complex projects on time.