Job Description
Are you ready to define the future of intelligence? Nexus Horizon Systems is seeking a visionary Senior AI & Machine Learning Engineer to join our elite engineering team in San Francisco. As we pioneer next-generation algorithms for the year 2026 and beyond, we need a technical leader who thrives on complexity and innovation.
In this role, you will not just write code; you will architect the neural networks that power our core products. We are looking for a self-starter who is passionate about Deep Learning, NLP, and scalable infrastructure. If you are ready to push the boundaries of what is possible in artificial intelligence, we want to hear from you.
Why join us?
- Work on cutting-edge AI projects with global impact.
- Competitive compensation package and equity options.
- Flexible remote-first culture with a vibrant San Francisco office.
Don't miss your chance to lead the technological revolution.
Responsibilities
- Design, develop, and deploy state-of-the-art machine learning models and algorithms to solve complex business problems.
- Lead the architecture and implementation of scalable AI infrastructure on cloud platforms (AWS/GCP/Azure).
- Collaborate with cross-functional teams of data scientists, engineers, and product managers to drive product innovation.
- Mentor junior engineers and conduct code reviews to ensure high standards of technical excellence.
- Optimize existing models for speed, accuracy, and resource efficiency in production environments.
- Stay abreast of the latest research in AI/ML to integrate new methodologies into our tech stack.
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, deep learning, or data science.
- Strong proficiency in programming languages such as Python, C++, or Java.
- Deep understanding of machine learning frameworks (TensorFlow, PyTorch, Keras) and libraries (scikit-learn, Pandas).
- Experience with distributed computing, MLOps, and cloud deployment practices.
- Proven track record of shipping production-grade AI products.