Job Description
Join the Pioneers of Tomorrow
Are you ready to architect the technological landscape of the future? Future Systems Inc. is seeking a visionary Senior AI Architect to lead the development of Project 2026, our groundbreaking predictive intelligence platform. In this role, you won't just be writing code; you will be defining the standards for how artificial intelligence integrates into the fabric of tomorrow's infrastructure.
We are looking for a thought leader who thrives in ambiguity and possesses the technical prowess to turn sci-fi concepts into scalable, real-world solutions. You will be at the helm of our core research division, bridging the gap between theoretical neural networks and practical, high-impact applications.
Why Join Us?
- Work on next-generation AI infrastructure that impacts millions.
- Competitive equity package and top-tier benefits.
- Flexible remote-first culture with a hub in the heart of SF.
Responsibilities
- Design and implement the core neural network architectures for Project 2026, ensuring scalability and fault tolerance.
- Lead a team of brilliant engineers and researchers in pushing the boundaries of generative AI and predictive modeling.
- Optimize existing models for reduced latency and improved accuracy in real-time data processing environments.
- Collaborate with product strategists to translate complex technical requirements into user-centric AI features.
- Establish best practices for data governance, security, and ethical AI implementation.
- Mentor junior developers and conduct code reviews to maintain high technical standards across the organization.
Qualifications
- Master’s degree or PhD in Computer Science, Mathematics, or a related field (or equivalent experience).
- 8+ years of professional experience in software engineering, with a minimum of 4 years specializing in AI/ML.
- Deep expertise in Python, PyTorch, TensorFlow, or JAX.
- Proven track record of deploying large-scale machine learning models into production.
- Strong understanding of distributed systems, cloud infrastructure (AWS/GCP/Azure), and containerization (Docker/Kubernetes).
- Familiarity with LLMs (Large Language Models) and transformer architectures is highly preferred.