Job Description
Shape the Future of Intelligence. Apex Horizon Technologies is at the forefront of the 2026 Vision Initiative, a groundbreaking project designed to pioneer the next generation of generative AI and autonomous systems. We are looking for a visionary Senior AI Architect to lead our technical strategy, designing scalable architectures that will define the AI landscape of the coming decade.
As a key member of our elite engineering team, you will bridge the gap between theoretical research and production-grade deployment. You will work in a fast-paced, high-impact environment where your code will power millions of interactions daily.
Why Join Us?
- Equity Package: Competitive stock options in a Series B startup poised for explosive growth.
- Remote-First Culture: Flexible work arrangements with a focus on output over hours.
- Top-Tier Tech Stack: Access to the latest GPUs, cloud infrastructure, and open-source frameworks.
- Impact: Direct ownership of core infrastructure that serves enterprise clients globally.
Responsibilities
- Architectural Design: Design and implement scalable, fault-tolerant AI infrastructure and model serving pipelines optimized for low latency and high throughput.
- Model Development: Lead the research and deployment of Large Language Models (LLMs) and generative models, focusing on fine-tuning, RAG (Retrieval-Augmented Generation), and reinforcement learning.
- MLOps Strategy: Define and build robust MLOps workflows to automate model training, validation, and deployment using CI/CD pipelines.
- Team Leadership: Mentor junior engineers and data scientists, conducting code reviews, architectural reviews, and technical workshops.
- Performance Optimization: Continuously monitor and optimize model inference performance, reducing costs while improving accuracy.
- Collaboration: Work closely with product managers, researchers, and designers to translate complex business requirements into technical solutions.
Qualifications
- Education: Master’s or Ph.D. in Computer Science, Machine Learning, or a related quantitative field (or equivalent practical experience).
- Experience: 5+ years of professional experience in AI/ML engineering, with at least 2 years in a senior or lead architecture role.
- Programming: Proficiency in Python, C++, or Rust. Strong understanding of software engineering best practices.
- Frameworks: Deep expertise in PyTorch, TensorFlow, JAX, or Hugging Face Transformers.
- Infrastructure: Experience with cloud platforms (AWS/GCP/Azure) and containerization technologies (Docker, Kubernetes).
- Problem Solving: Proven track record of solving complex technical challenges in high-scale production environments.
- Communication: Excellent verbal and written communication skills, capable of presenting complex technical concepts to non-technical stakeholders.