Job Description
Are you ready to architect the future of intelligence?
Nexus Horizon Systems is pioneering the next generation of autonomous agents and multimodal AI systems. We are looking for a visionary Senior AI/ML Architect to lead our R&D initiatives for our 2026 product roadmap. In this role, you will define the architectural backbone of our platform, ensuring scalability, security, and innovation that pushes the boundaries of what is possible in Generative AI.
You will work at the intersection of deep learning, MLOps, and product engineering, collaborating with world-class researchers and engineers to deploy solutions that impact millions.
Why Join Us?
- Impactful Work: Build the foundational models that power the next decade of tech.
- Future-Proof: Shape our strategy for the 2026 landscape, focusing on ethical AI and human-AI symbiosis.
- Top-Tier Team: Work alongside industry leaders in AI, distributed systems, and cloud infrastructure.
Responsibilities
- Lead the architectural design and development of proprietary Large Language Models (LLMs) and Agentic workflows targeted for the 2026 market release.
- Design scalable machine learning pipelines and data ingestion strategies to handle petabyte-scale data sets.
- Drive the implementation of advanced MLOps practices, including automated retraining, A/B testing, and model monitoring.
- Collaborate with cross-functional teams (Product, Engineering, Legal) to ensure AI solutions are compliant, explainable, and aligned with ethical guidelines.
- Mentor junior engineers and data scientists, fostering a culture of technical excellence and innovation.
- Research emerging technologies in computer vision, NLP, and reinforcement learning to integrate into our core stack.
Qualifications
- Master’s or PhD in Computer Science, Machine Learning, or a related quantitative field (or equivalent practical experience).
- 10+ years of experience in software engineering, with at least 5 years specifically focused on Machine Learning and AI systems architecture.
- Deep expertise in Python, PyTorch, TensorFlow, or JAX.
- Proven experience building and deploying LLMs, transformers, or generative models at scale.
- Strong understanding of distributed systems, cloud architecture (AWS/GCP/Azure), and containerization technologies (Docker, Kubernetes).
- Experience with data engineering tools (Spark, Kafka, SQL) and vector databases (Pinecone, Milvus).