Job Description
Join Nexus Horizon, a pioneer in next-generation artificial intelligence, as we architect the systems of tomorrow for the year 2026 and beyond. We are looking for a visionary Senior AI/ML Engineer to lead the development of autonomous agents, generative AI infrastructures, and predictive modeling frameworks that will redefine human-machine interaction.
In this role, you will bridge the gap between theoretical machine learning breakthroughs and scalable production systems. You will work in a high-performance environment focused on ethical AI, deep learning optimization, and building the intelligent core of our future platform.
Why Nexus Horizon?
- Work on cutting-edge projects that shape the future of technology.
- Competitive compensation package with equity options.
- Flexible remote-first policy with state-of-the-art office amenities in downtown SF.
- Access to the latest hardware and cloud infrastructure.
Responsibilities
- Lead Model Architecture: Design, implement, and deploy advanced deep learning models, focusing on LLMs, Transformers, and reinforcement learning agents for 2026 readiness.
- System Optimization: Drive performance engineering to reduce latency and increase inference throughput for real-time AI applications.
- Research & Innovation: Stay at the forefront of AI trends, conducting research and prototyping novel algorithms to solve complex business problems.
- Collaboration: Partner with data scientists, software engineers, and product managers to translate technical requirements into scalable solutions.
- Scalability: Architect ML pipelines that can handle petabyte-scale data efficiently using cloud-native technologies.
- Mentorship: Guide junior engineers and data scientists, fostering a culture of technical excellence and continuous learning.
Qualifications
- Education: Master’s or PhD in Computer Science, Mathematics, Statistics, or a related technical field.
- Experience: 5+ years of professional experience in machine learning engineering, with a strong portfolio of deployed models.
- Core Skills: Proficiency in Python, PyTorch, TensorFlow, or JAX. Deep understanding of NLP, Computer Vision, or Predictive Analytics.
- Infrastructure: Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
- Problem Solving: Ability to debug complex distributed systems and optimize computational graphs.
- Communication: Excellent verbal and written communication skills for technical documentation and stakeholder presentations.