Job Description
Are you ready to define the future of Intelligence?
Nexus Horizon is pioneering the next generation of autonomous AI agents. We are looking for a visionary Senior AI/ML Engineer to lead the development of cutting-edge Large Language Models (LLMs) and multimodal systems. If you thrive in a fast-paced, high-impact environment and want to build the technology that will power the world in 2026 and beyond, we want to talk to you.
Why Join Us?
- Impact First: Your code will directly influence billions of interactions.
- Rewards: Competitive salary, equity packages, and comprehensive benefits.
- Environment: Collaborate with world-class researchers and engineers.
Apply today and help us build the brain of tomorrow.
Responsibilities
- Model Development: Design, train, and fine-tune state-of-the-art Large Language Models (LLMs) and diffusion models.
- Infrastructure Optimization: Engineer high-performance inference pipelines and optimize model serving latency on GPU clusters.
- RAG Architecture: Build robust Retrieval-Augmented Generation systems to enhance factual accuracy and reduce hallucinations.
- Research & Innovation: Stay at the forefront of AI research, implementing novel architectures and techniques.
- Collaboration: Work closely with product teams to translate technical requirements into scalable AI solutions.
- MLOps: Establish CI/CD pipelines for model deployment and continuous monitoring of model performance.
Qualifications
- Education: MS or PhD in Computer Science, Mathematics, or a related field.
- Experience: 5+ years of professional experience in Machine Learning, Deep Learning, or Natural Language Processing.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, and Hugging Face Transformers.
- Tools: Experience with distributed training frameworks (Ray, Horovod) and cloud platforms (AWS, GCP).
- Language: Strong command of English, with the ability to communicate complex technical concepts clearly.
- Problem Solving: Demonstrated ability to tackle complex optimization problems and debug intricate model behaviors.