Job Description
We are on the cutting edge of defining the technological landscape of 2026. At Apex Future Systems, we are not just predicting the future; we are architecting it. We are seeking a visionary Senior AI Architect to lead the design and implementation of our next-generation generative AI platform. In this high-impact role, you will be responsible for building the infrastructure that powers our products for the upcoming decade. Join us in shaping the intelligent systems of tomorrow.
Why Join Us?
- Impact: Directly influence the technical roadmap for our 2026 release.
- Equity: Competitive equity package for key leadership roles.
- Environment: Work with a world-class team of engineers and researchers.
Responsibilities
- Architect and design scalable, high-performance machine learning infrastructure tailored for the 2026 technology stack.
- Lead the end-to-end development of Generative AI models, including LLMs and multimodal systems.
- Define technical standards, best practices, and coding guidelines for the AI engineering team.
- Collaborate with product managers and stakeholders to translate business requirements into technical solutions.
- Mentor junior engineers and conduct code reviews to ensure code quality and architectural integrity.
- Optimize existing models for speed, accuracy, and resource efficiency.
- Stay ahead of industry trends in AI research to ensure our technology remains at the forefront.
Qualifications
- Master’s or PhD degree in Computer Science, Artificial Intelligence, or a related technical field.
- 10+ years of experience in software engineering and 5+ years specifically in AI/ML architecture.
- Deep expertise in Python, PyTorch, TensorFlow, or JAX.
- Proven experience deploying large-scale machine learning models into production environments.
- Strong understanding of distributed systems, cloud architecture (AWS/Azure/GCP), and MLOps.
- Excellent problem-solving skills and the ability to thrive in a fast-paced, startup environment.
- Experience with ethical AI practices and responsible machine learning deployment.