Job Description
Are you ready to architect the next generation of intelligent systems? Nexus Horizon AI is pioneering the frontier of Artificial General Intelligence (AGI) and generative modeling for the year 2026 and beyond. We are seeking a visionary Senior AI/ML Engineer to lead the development of scalable, robust, and ethical AI solutions that redefine human-machine interaction.
In this role, you will not just implement existing models; you will push the boundaries of what is possible in Large Language Models (LLMs), Reinforcement Learning from Human Feedback (RLHF), and Edge AI deployment. If you thrive in a fast-paced, high-impact environment and possess a deep understanding of mathematical foundations combined with cutting-edge engineering practices, we want to meet you.
Why Join Us?
- Work on projects that will shape the future of technology.
- Competitive compensation and equity package.
- Flexible hybrid work model in the heart of San Francisco.
- Access to state-of-the-art hardware and research tools.
Responsibilities
- Design, train, and fine-tune state-of-the-art Large Language Models (LLMs) and multimodal architectures.
- Develop and optimize high-performance ML pipelines using PyTorch and TensorFlow, ensuring low latency and high throughput.
- Implement advanced Reinforcement Learning (RL) strategies to improve model alignment and reasoning capabilities.
- Collaborate with cross-functional teams of data scientists, engineers, and product managers to translate research into production-ready applications.
- Conduct rigorous experimentation and A/B testing to validate model improvements and drive business metrics.
- Mentor junior engineers and contribute to the technical roadmap for AI infrastructure.
- Ensure the scalability, security, and ethical deployment of AI models in cloud and edge environments.
Qualifications
- Master’s or PhD in Computer Science, Mathematics, or a related field (or equivalent professional experience).
- 5+ years of professional experience in Machine Learning, Deep Learning, or Natural Language Processing.
- Deep expertise in training and fine-tuning transformer-based models (e.g., GPT, BERT, Llama variants).
- Proficiency in Python, C++, and modern ML frameworks (PyTorch, TensorFlow, JAX).
- Strong understanding of MLOps practices, including model versioning, CI/CD for ML, and deployment on Kubernetes.
- Experience with distributed computing frameworks (Apache Spark, Ray) is highly desirable.
- Exceptional problem-solving skills and the ability to communicate complex technical concepts to non-technical stakeholders.