Job Description
Join the Architects of the Future.
We are seeking a visionary Senior AI Architect to lead our R&D division focused on the next generation of autonomous intelligence systems. As we look toward the 2026 horizon, we are building the infrastructure for a world where Generative AI is not just a tool, but an autonomous partner. If you are passionate about pushing the boundaries of Large Language Models (LLMs), Reinforcement Learning, and Agentic Workflows, this is your opportunity to define the standard.
Why Apex Horizon?
Our mission is to democratize super-intelligence. We offer a competitive benefits package, equity, and the chance to work with a team of world-class engineers and researchers.
Responsibilities
- Architect Next-Gen Models: Design and deploy scalable, high-performance LLM architectures capable of complex reasoning and autonomous task execution.
- Optimization & Efficiency: Implement advanced quantization techniques and inference optimization strategies to reduce latency and cost for real-time applications.
- Agentic Workflow Integration: Build systems that integrate multi-agent frameworks to automate complex enterprise workflows with zero human intervention.
- Research & Development: Stay ahead of the curve on emerging AI paradigms, including multimodal learning and causal inference models.
- MLOps Infrastructure: Oversee the deployment pipeline, ensuring robust monitoring, A/B testing, and CI/CD for production AI models.
- Cross-Functional Leadership: Mentor junior engineers and collaborate with product teams to translate technical possibilities into market-ready solutions.
Qualifications
- Education: MS or PhD in Computer Science, Machine Learning, or a related technical field from a top-tier university.
- Core Tech Stack: Deep proficiency in Python, PyTorch, TensorFlow, and Hugging Face Transformers.
- Model Expertise: Proven experience fine-tuning open-source models (Llama 3, Mistral, Falcon) and optimizing them for specific verticals.
- Experience: 5+ years of experience in Machine Learning Engineering, with at least 2 years focusing specifically on Generative AI or NLP.
- System Design: Strong understanding of distributed systems, GPU clusters, and cloud infrastructure (AWS/GCP/Azure).
- Creative Problem Solving: Ability to troubleshoot complex, non-deterministic AI behaviors and develop robust fallback strategies.