Job Description
We are looking for a visionary Senior AI & Machine Learning Architect to lead our team in defining the technological landscape for the Year 2026. At Apex Future Systems, we don't just build software; we architect the future of human-machine interaction. You will be at the forefront of developing autonomous agents and scalable neural networks designed to solve the complex challenges of tomorrow.
As a key member of our R&D division, you will bridge the gap between theoretical research and production-grade engineering, ensuring our platforms are robust, scalable, and ethically sound.
Why Join Us?
- Work on cutting-edge AI infrastructure that prepares the industry for the next decade.
- Competitive compensation package including equity options.
- Flexible remote-first policy with a hub in the heart of San Francisco.
- Access to state-of-the-art computing resources and research grants.
Responsibilities
- Architect and deploy scalable machine learning models with a focus on Generative AI and Large Language Models (LLMs).
- Lead the research and implementation of next-generation algorithms for autonomous decision-making systems.
- Collaborate with product teams to define technical roadmaps aligned with the 2026 strategic vision.
- Optimize model inference latency and reduce computational costs for large-scale deployments.
- Establish best practices for data privacy, security, and ethical AI usage.
- Mentor junior engineers and foster a culture of innovation and continuous learning.
Qualifications
- Master’s or Ph.D. in Computer Science, Artificial Intelligence, or a related quantitative field.
- 7+ years of professional experience in machine learning, deep learning, and natural language processing.
- Proven expertise in Python, PyTorch, TensorFlow, or JAX.
- Experience designing and fine-tuning Large Language Models (LLMs) for enterprise applications.
- Strong understanding of distributed systems and cloud architecture (AWS, GCP, or Azure).
- Excellent problem-solving skills and the ability to communicate complex technical concepts to non-technical stakeholders.