Job Description
We are on a mission to define the technological landscape of 2026 and beyond. Apex Horizon Technologies is seeking a visionary Senior AI Architect to lead our research into Generative AI, Autonomous Agents, and Next-Gen Neural Networks. If you are passionate about building systems that will shape the future and possess the expertise to bridge the gap between theoretical AI and scalable production infrastructure, we want to meet you.
In this role, you won't just be maintaining existing systems; you will be architecting the core intelligence that drives our products. You will work in a high-performance environment alongside top-tier researchers and engineers, pushing the boundaries of what is possible with Large Language Models (LLMs) and multimodal AI systems.
Why Join Us?
- Future-Forward Impact: Your work will directly influence the roadmap for 2026.
- Top-Tier Compensation: Competitive salary and equity package.
- State-of-the-Art Infrastructure: Access to cutting-edge compute resources and GPUs.
Responsibilities
- Design and deploy scalable AI infrastructure capable of handling billions of parameters and real-time inference.
- Lead the research and development of novel machine learning algorithms, focusing on efficiency and accuracy for 2026 standards.
- Collaborate with cross-functional teams to integrate AI models into consumer and enterprise products.
- Oversee the training pipeline, ensuring data integrity and model performance optimization.
- Mentor junior engineers and researchers, fostering a culture of innovation and technical excellence.
- Stay ahead of industry trends, specifically in Agentic AI and Neural Architecture Search.
Qualifications
- Ph.D. or Master’s degree in Computer Science, Artificial Intelligence, or a related field.
- 7+ years of professional experience in machine learning engineering or applied AI research.
- Deep expertise in Python, PyTorch, TensorFlow, or JAX.
- Proven track record of deploying large-scale LLMs and Transformer architectures.
- Experience with MLOps tools (Docker, Kubernetes, MLflow) and cloud platforms (AWS/GCP/Azure).
- Strong understanding of ethical AI, bias mitigation, and responsible machine learning practices.
- Excellent problem-solving skills and ability to thrive in fast-paced, ambiguous environments.