Job Description
Are you ready to define the future of intelligence? Nexus Horizon is pioneering the next generation of Generative AI solutions, and we are seeking a visionary Senior AI Engineer to join our elite engineering team in San Francisco.
In this pivotal role, you will not just build models; you will architect the neural frameworks that power our industry-leading products. You will work at the intersection of deep learning, natural language processing, and scalable cloud infrastructure. If you are passionate about pushing the boundaries of what is possible with AI and want to make a tangible impact on the world, we want to meet you.
Why Join Nexus Horizon?
- Impactful Work: Deploy AI models that are used by millions globally.
- Top-Tier Compensation: Competitive salary, equity packages, and comprehensive benefits.
- Modern Stack: Work with PyTorch, TensorFlow, and cutting-edge GPU infrastructure.
We are looking for a self-starter who thrives in a fast-paced, innovative environment.
Responsibilities
- Design, train, and deploy state-of-the-art deep learning models and LLMs.
- Optimize model inference latency and throughput for real-time applications.
- Collaborate with data scientists and product managers to translate business requirements into technical AI solutions.
- Mentor junior engineers and foster a culture of technical excellence and continuous learning.
- Research and implement novel techniques in NLP, Computer Vision, or Reinforcement Learning.
- Ensure model scalability, robustness, and ethical AI practices.
Qualifications
- Ph.D. or Master’s degree in Computer Science, Mathematics, or a related field.
- 5+ years of professional experience in machine learning and deep learning.
- Strong proficiency in Python, PyTorch, or TensorFlow.
- Extensive experience with distributed training frameworks (e.g., Ray, Horovod).
- Deep understanding of MLOps practices, CI/CD pipelines, and cloud platforms (AWS/GCP/Azure).
- Proven track record of publishing in top-tier conferences (NeurIPS, ICML, ACL) or shipping production-grade models.