Job Description
Join FutureScale Inc., a pioneer in next-generation artificial intelligence, as our Lead AI Architect. We are not just building software for today; we are architecting the infrastructure for the year 2026. In this pivotal role, you will define the technical roadmap for our upcoming generative intelligence suite, focusing on scalable neural networks, autonomous agents, and ethical AI frameworks.
As we approach the 2026 technological horizon, we need a visionary leader who can translate complex theoretical models into robust, production-ready systems. You will work closely with our CTO and engineering teams to pioneer breakthroughs in Large Language Models (LLMs) and predictive analytics.
Why Join Us?
- Shape the future of human-computer interaction.
- Work with cutting-edge hardware and software stacks.
- Competitive compensation and equity packages.
Responsibilities
- Strategic Roadmap: Define and execute the technical vision for AI infrastructure, ensuring alignment with the company’s 2026 product goals.
- System Architecture: Design scalable, fault-tolerant systems capable of handling exabyte-scale data processing.
- R&D Leadership: Lead a team of top-tier engineers in researching and implementing state-of-the-art algorithms, including transformers and reinforcement learning.
- Model Optimization: Oversee the fine-tuning and deployment of LLMs, ensuring high performance and low latency.
- Cross-Functional Collaboration: Partner with product managers, data scientists, and stakeholders to bridge the gap between theoretical AI and practical application.
- Compliance & Ethics: Establish rigorous standards for AI safety, bias mitigation, and data privacy.
Qualifications
- Education: Master’s or Ph.D. in Computer Science, Artificial Intelligence, or a related technical field.
- Experience: 10+ years of experience in software engineering, with at least 5 years specifically in AI/ML architecture.
- Technical Stack: Deep expertise in Python, TensorFlow, PyTorch, and distributed computing frameworks (Kubernetes, Spark).
- Domain Knowledge: Proven track record of deploying large-scale machine learning models in production environments.
- Leadership: Demonstrated ability to lead high-performing engineering teams and drive technical decision-making.
- Future-Forward Mindset: Passionate about emerging technologies and a keen interest in the technological trends shaping 2026 and beyond.