Job Description
We are looking for a visionary Senior Machine Learning Engineer to join our elite AI division. As we prepare for the next era of artificial intelligence, we are building the architecture that will define the technology landscape of 2026 and beyond. You will work at the intersection of deep learning, natural language processing, and scalable infrastructure to deploy next-generation generative models.
In this role, you will not just use existing tools; you will help build the future. You will be responsible for training, fine-tuning, and deploying state-of-the-art Large Language Models (LLMs) and multimodal architectures that power our enterprise clients. If you are passionate about the future of AI and want to leave a lasting impact, we want to hear from you.
Why join Nexus Horizon?
- Work on cutting-edge AI projects with a team of world-class researchers.
- Competitive salary and equity packages.
- Flexible remote-first policy with a vibrant NYC office.
- Access to the latest hardware and cloud resources.
Responsibilities
- Model Development: Architect and train proprietary Generative AI models, focusing on LLMs and diffusion models, tailored for high-performance enterprise applications.
- R&D Leadership: Stay ahead of the curve on the latest research in Deep Learning, implementing novel architectures to improve model accuracy and efficiency.
- Infrastructure & MLOps: Design scalable pipelines for training, fine-tuning, and serving models using tools like Kubernetes, Docker, and MLflow.
- Ethical AI: Implement robust guardrails and safety measures to ensure model outputs are unbiased, safe, and compliant with industry regulations.
- Collaboration: Partner with product managers and data scientists to translate complex business requirements into technical AI solutions.
Qualifications
- Education: Master’s or PhD in Computer Science, Mathematics, or a related field (or equivalent practical experience).
- Experience: 5+ years of professional experience in Machine Learning, Deep Learning, or Natural Language Processing.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, or JAX. Experience with Hugging Face Transformers and model fine-tuning is required.
- Tools: Strong understanding of MLOps practices, cloud platforms (AWS/GCP/Azure), and containerization technologies.
- Language: Excellent written and verbal communication skills in English.