Job Description
Shape the Future of Intelligence.
Nexus Horizon is at the forefront of the next technological revolution. We are seeking a visionary Senior Generative AI Engineer to lead the development of scalable Large Language Models (LLMs) and multimodal AI systems. If you are passionate about pushing the boundaries of artificial intelligence and want to define the standards for 2026 and beyond, we want to hear from you.
In this role, you will bridge the gap between cutting-edge research and production-grade applications, optimizing models for latency, cost, and accuracy. You will work in a collaborative, remote-first environment with a team of world-class researchers and engineers.
Why Join Us?
- Impactful Work: Deploy AI solutions that solve real-world problems at scale.
- Future-Proof: Work with the latest frameworks (PyTorch, TensorFlow) and emerging architectures (Transformers, GNNs).
- Equity Package: Competitive stock options in a high-growth startup environment.
- Flexible Culture: Fully remote-first with generous PTO and wellness stipends.
Responsibilities
- Model Development: Design, train, and fine-tune state-of-the-art generative models using Transformer architectures and reinforcement learning from human feedback (RLHF).
- Infrastructure Optimization: Build and maintain high-throughput inference pipelines, leveraging GPU clusters and model serving frameworks like vLLM or TGI.
- Research Implementation: Translate academic research papers into production-ready code and evaluate novel architectures for specific business use cases.
- Code Quality & Architecture: Write clean, maintainable code following best practices, and mentor junior engineers on MLOps and software engineering principles.
- Performance Tuning: Conduct rigorous testing to reduce latency and memory footprint while maintaining model fidelity.
Qualifications
- Education: Master’s or PhD in Computer Science, Machine Learning, or a related field (4+ years of equivalent industry experience accepted).
- Technical Expertise: Deep proficiency in Python, PyTorch, or TensorFlow. Experience with Hugging Face Transformers and LangChain is required.
- Production Experience: Proven track record of deploying large-scale machine learning models to cloud environments (AWS/GCP/Azure).
- MLOps: Familiarity with MLflow, Docker, Kubernetes, and CI/CD pipelines for machine learning.
- Problem Solving: Strong ability to debug complex distributed systems and optimize resource utilization.