Job Description
Are you ready to define the future of Artificial Intelligence? Nexus Horizon Technologies is on the hunt for a visionary Senior AI Engineer to lead our flagship Project 2026. As a pioneer in next-gen generative AI and neural architectures, we are building the systems that will power enterprise decision-making for the decade ahead.
In this role, you won't just implement existing models; you will architect the future. You will work in a high-performance environment, pushing the boundaries of Large Language Models (LLMs) and predictive analytics. If you are passionate about solving complex problems and have a track record of deploying scalable AI solutions, we want to meet you.
Why Join Nexus Horizon?
- Impactful Work: Directly contribute to Project 2026, a transformative initiative aimed at revolutionizing industry standards.
- Competitive Package: Top-tier compensation and equity packages tailored for senior talent.
- Modern Stack: Work with the latest in PyTorch, TensorFlow, and cloud-native infrastructure.
Join us in San Francisco and help us build the intelligent systems of tomorrow.
Responsibilities
- Lead the architectural design and implementation of complex AI models for Project 2026, ensuring high scalability and performance.
- Collaborate with cross-functional teams of data scientists, engineers, and product managers to translate business requirements into technical AI solutions.
- Optimize existing models for inference speed and reduce latency in production environments.
- Conduct rigorous research into novel deep learning techniques and evaluate their feasibility for integration into the core platform.
- Implement and maintain robust CI/CD pipelines for machine learning models, ensuring reproducibility and reliability.
- Mentor junior engineers and data scientists, fostering a culture of technical excellence and innovation.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Mathematics, Physics, or a related field (PhD preferred).
- Minimum of 5+ years of professional experience in Machine Learning Engineering or Applied AI.
- Deep expertise in Python, PyTorch, and/or TensorFlow.
- Proven track record of deploying and serving large-scale machine learning models in production.
- Strong understanding of Natural Language Processing (NLP) and Large Language Models (LLMs).
- Experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Excellent problem-solving skills and the ability to thrive in a fast-paced, agile environment.