Job Description
Are you ready to define the technological landscape of the year 2026? FutureScale Systems is seeking a visionary Senior AI Architect to lead our 2026 Horizon Initiative.
In this pivotal role, you will be at the forefront of deploying next-generation Artificial Intelligence, Large Language Models (LLMs), and autonomous agent frameworks. We are building the infrastructure that will power the digital economy a decade from now, and we need an expert who can bridge the gap between theoretical research and production-grade engineering.
Why join the 2026 Horizon Initiative?
- Work on cutting-edge generative AI technologies.
- Shape the future of enterprise automation.
- Competitive compensation and equity packages.
We are looking for a leader who is not just proficient in current stacks but is obsessed with the evolution of technology.
Responsibilities
- Architect Scalable AI Solutions: Design and implement robust machine learning infrastructure capable of handling petabyte-scale data and high-throughput inference.
- Lead Research & Development: Spearhead the research into emerging AI paradigms, focusing on multimodal learning and real-time decision-making systems.
- Optimize Model Performance: Continuously fine-tune and optimize models for latency, accuracy, and cost-efficiency in production environments.
- Cross-Functional Collaboration: Partner with product managers and data scientists to translate complex business requirements into technical roadmaps.
- Code Quality & Mentorship: Establish best practices for MLOps, CI/CD, and code review while mentoring junior engineers and data scientists.
Qualifications
- Education: Master’s or Ph.D. in Computer Science, Machine Learning, or a related quantitative field from a top-tier institution.
- Experience: 7+ years of professional experience in software engineering, with at least 4 years specifically focused on AI/ML architecture.
- Technical Stack: Deep proficiency in Python, PyTorch, TensorFlow, and experience with distributed computing frameworks (e.g., Apache Spark, Ray).
- MLOps: Extensive experience with cloud platforms (AWS/GCP), containerization (Docker/Kubernetes), and model serving pipelines.
- Problem Solving: Demonstrated ability to solve complex, ambiguous problems in novel ways.