Job Description
Join the vanguard of artificial intelligence. Nexus Horizon Systems is seeking a visionary Senior AI Engineer to spearhead our revolutionary Project 2026. This is not just a job; it is an opportunity to architect the future of adaptive learning systems and predictive intelligence.
In this pivotal role, you will lead the development of next-generation neural architectures designed to solve complex, real-world challenges. You will work in a dynamic, high-performance environment alongside world-class researchers and engineers. If you are passionate about pushing the boundaries of what is possible with Machine Learning and Deep Learning, we want to hear from you.
Why Nexus Horizon?
- Competitive compensation package with equity options.
- Access to cutting-edge hardware and cloud infrastructure.
- Flexible remote-first culture with a vibrant hub in Austin.
Ready to shape the future? Apply today.
Responsibilities
- Lead R&D: Architect and implement advanced Machine Learning models for Project 2026, focusing on scalability and real-time inference.
- Model Optimization: Optimize existing models for reduced latency and improved accuracy, ensuring high performance under heavy load.
- Team Leadership: Mentor junior engineers and data scientists, conducting code reviews and architectural discussions.
- Collaboration: Work closely with product managers and domain experts to translate business requirements into technical AI solutions.
- Deployment: Oversee the deployment of models into production environments using MLOps best practices.
- Research: Stay abreast of the latest developments in the AI space and integrate novel techniques into our framework.
Qualifications
- Education: Master’s or PhD in Computer Science, Mathematics, or a related field (or equivalent professional experience).
- Experience: 5+ years of professional experience in building and deploying production-grade Machine Learning systems.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, or JAX.
- Big Data: Strong experience with distributed computing frameworks (Spark, Hadoop) and data processing tools (Pandas, NumPy).
- Cloud: Hands-on experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
- Problem Solving: Demonstrated ability to tackle ambiguous problems and derive data-driven insights.