Job Description
Are you ready to architect the future of intelligent systems? Nexus Horizon Technologies is seeking a visionary Senior Generative AI Engineer to lead our next-generation multimodal model initiatives. In this pivotal role, you will define the technical roadmap for our AI products, pushing the boundaries of what is possible with Large Language Models (LLMs) and diffusion systems. Join a team of elite engineers and researchers dedicated to solving the world's most complex challenges through advanced artificial intelligence.
Why Join Us?
We are building the infrastructure for tomorrow. You will work with state-of-the-art hardware, collaborate with top-tier talent, and have direct impact on products used by millions. We offer competitive compensation, equity packages, and a culture that prioritizes innovation and ethical AI development.
Responsibilities
- Design, train, and fine-tune large-scale generative AI models, including LLMs and diffusion models, to achieve state-of-the-art performance on complex tasks.
- Optimize model inference pipelines for speed and cost-efficiency, deploying scalable solutions on cloud infrastructure (AWS/GCP).
- Conduct cutting-edge research to explore new architectures, training methodologies, and evaluation metrics for generative AI.
- Collaborate with cross-functional teams of product managers, data scientists, and engineers to translate research into production-ready features.
- Ensure the ethical, safe, and responsible deployment of AI systems, adhering to regulatory standards and internal guidelines.
- Mentor junior engineers and data scientists, fostering a culture of continuous learning and technical excellence within the AI research group.
Qualifications
- Master’s or Ph.D. degree in Computer Science, Machine Learning, Mathematics, or a related field, or equivalent practical experience.
- Deep expertise in deep learning frameworks such as PyTorch, TensorFlow, or JAX, with proven experience in training LLMs.
- Strong background in natural language processing (NLP), computer vision, or reinforcement learning.
- Experience with MLOps, model serving (e.g., TensorFlow Serving, TorchServe), and cloud-native deployment.
- Excellent problem-solving skills and the ability to work independently in a fast-paced, ambiguous environment.
- Strong communication skills, with the ability to articulate complex technical concepts to both technical and non-technical stakeholders.