Job Description
Are you a visionary engineer ready to shape the future of artificial intelligence? Nexus Horizon Labs is seeking a world-class Senior Generative AI Engineer to lead the development of next-generation Large Language Models (LLMs) and multimodal systems. Join a team of elite engineers and researchers dedicated to pushing the boundaries of what's possible in 2026 and beyond.
Why Join Us?
We offer a competitive compensation package, equity opportunities, and the chance to work on projects that redefine industry standards. You will have the autonomy to design scalable architectures and the resources to experiment with cutting-edge research.
The Role:
You will be responsible for the full lifecycle of AI model development, from research and prototyping to deployment and monitoring at scale. You will collaborate closely with product teams to integrate AI capabilities into robust, user-centric applications.
Responsibilities
- Model Architecture: Design and implement novel generative AI architectures, specifically focusing on LLMs and diffusion models.
- Optimization: Optimize model inference speed and reduce latency for real-time applications.
- Training Pipeline: Build and maintain scalable training pipelines using distributed computing frameworks.
- Deployment: Deploy models to production environments using containerization (Docker/Kubernetes) and cloud infrastructure (AWS/GCP).
- Evaluation: Establish rigorous evaluation metrics to measure model performance, bias, and safety.
- Collaboration: Work cross-functionally with data scientists, product managers, and designers to translate technical requirements into user features.
Qualifications
- Experience: 5+ years of experience in software engineering, with at least 3 years specializing in Machine Learning or AI.
- Technical Skills: Proficiency in Python, PyTorch, or TensorFlow.
- Domain Knowledge: Deep understanding of Natural Language Processing (NLP), transformers, and generative models.
- Infrastructure: Strong experience with MLOps tools, cloud platforms, and CI/CD pipelines.
- Education: Bachelor’s degree in Computer Science, Mathematics, or a related field (Master’s degree preferred).
- Problem Solving: Proven ability to solve complex engineering challenges and optimize system performance.