Job Description
Are you ready to define the technological landscape of 2026 and beyond? FutureScale Systems is on the hunt for a visionary Senior AI Architect to lead our next-generation neural network initiatives. We are not just building software; we are engineering the cognitive core of tomorrow's industries. If you thrive in high-stakes environments and possess an uncanny ability to bridge the gap between theoretical AI and practical application, we want to meet you.
In this pivotal role, you will be responsible for architecting scalable, fault-tolerant machine learning systems that power our autonomous solutions. You will work directly with C-level executives and engineering leads to steer our product roadmap toward a future-proof ecosystem.
Why Join Us?
- Work on cutting-edge Generative AI and Autonomous Agents.
- Competitive equity package and health benefits.
- Flexible remote and hybrid work options.
- Access to top-tier hardware for R&D.
Responsibilities
- Architect System Design: Design and implement scalable AI architectures that can handle billions of data points with sub-millisecond latency.
- Model Optimization: Lead the research and deployment of state-of-the-art Large Language Models (LLMs) and computer vision algorithms.
- Team Leadership: Mentor a team of data scientists and ML engineers, fostering a culture of innovation and technical excellence.
- Strategic Roadmapping: Define the technical vision for AI integration across all product lines, ensuring alignment with 2026 business goals.
- Production Deployment: Oversee the MLOps pipeline, ensuring seamless CI/CD integration and model monitoring in production environments.
- Collaboration: Partner with cross-functional teams including Product, Security, and Backend Engineering to integrate AI seamlessly.
Qualifications
- Experience: 7+ years of experience in software engineering, with at least 4 years specifically in AI/ML architecture.
- Education: Master’s degree or PhD in Computer Science, Artificial Intelligence, or a related quantitative field.
- Technical Stack: Proficiency in Python, PyTorch, TensorFlow, and Kubernetes.
- Cloud Expertise: Deep understanding of cloud infrastructure (AWS, GCP, or Azure) and serverless computing models.
- Problem Solving: Proven track record of solving complex algorithmic problems in real-world scenarios.
- Communication: Exceptional ability to translate complex technical concepts for non-technical stakeholders.