Job Description
We are at the forefront of a technological renaissance, building the infrastructure for the AI-driven era of 2026. Apex Horizon Systems is seeking a visionary Senior AI Architect to lead the development of our next-generation autonomous intelligence systems. If you possess a deep understanding of machine learning, scalable architecture, and a passion for the ethical future of AI, we want to hear from you.
In this role, you will not just write code; you will define the architectural standards for the future. You will work with a world-class team of data scientists, engineers, and product strategists to deploy cutting-edge neural networks that solve complex global challenges.
Why join us?
- Work on mission-critical projects that define the industry standard.
- Competitive equity and a comprehensive benefits package.
- Access to state-of-the-art compute resources and R&D labs.
Responsibilities
- Architect and design scalable, high-performance AI infrastructure capable of processing petabytes of real-time data.
- Lead the research and implementation of next-generation deep learning algorithms, focusing on generative AI and reinforcement learning.
- Define technical roadmaps and best practices for the AI engineering team, ensuring code quality and scalability.
- Collaborate with product managers to translate complex business requirements into robust technical solutions.
- Oversee the deployment of models into production environments, optimizing for latency and accuracy.
- Mentor junior engineers and data scientists, fostering a culture of continuous innovation and learning.
- Stay ahead of the curve on emerging AI trends and technologies, specifically those relevant to the 2026 landscape.
Qualifications
- Master’s or PhD in Computer Science, Mathematics, or a related technical field (or equivalent practical experience).
- Minimum of 8+ years of experience in software engineering, with a minimum of 5 years specifically focused on AI/ML architecture.
- Deep expertise in Python, TensorFlow, PyTorch, and distributed computing frameworks (e.g., Kubernetes, Apache Spark).
- Proven track record of deploying large-scale machine learning models in production environments.
- Strong understanding of neural network architectures, natural language processing (NLP), and computer vision.
- Experience with cloud platforms (AWS, GCP, or Azure) and serverless architectures.
- Excellent problem-solving skills and the ability to thrive in a fast-paced, ambiguous environment.