Job Description
We are building the infrastructure for the year 2026 and beyond. At Apex Future Systems, we are looking for a visionary Lead AI Architect to spearhead the next generation of autonomous intelligence systems. This is not just a job; it is an opportunity to define the standard for artificial general intelligence (AGI) safety and scalability.
In this high-impact role, you will bridge the gap between theoretical machine learning breakthroughs and production-grade software engineering. You will lead a world-class team in designing neural architectures that are efficient, ethical, and capable of complex reasoning.
Why join us?
- Work on cutting-edge generative models and multi-agent systems.
- Competitive equity package reflecting our 2026 unicorn valuation.
- Flexible remote-first culture with a hub in San Francisco.
Responsibilities
- Architect and optimize scalable machine learning pipelines for high-volume inference.
- Lead research initiatives into next-generation Large Language Models (LLMs) and reinforcement learning agents.
- Collaborate with product teams to integrate AI capabilities into consumer and enterprise applications.
- Establish best practices for AI model monitoring, governance, and safety alignment.
- Define technical roadmaps for the AI infrastructure team, ensuring scalability for 2026 demands.
- Drive the adoption of novel hardware acceleration techniques (e.g., TPUs, NPUs).
Qualifications
- PhD or Master’s degree in Computer Science, Mathematics, or a related field with a focus on AI/ML.
- 8+ years of experience in software engineering with a specific focus on Machine Learning infrastructure.
- Deep expertise in PyTorch, TensorFlow, or JAX.
- Proven track record of deploying production-grade models handling petabytes of data.
- Experience with distributed systems (Kubernetes, Docker) and cloud platforms (AWS, GCP).
- Strong understanding of neural architecture search and model compression techniques.