Job Description
Architect the Future of AI
We are seeking a visionary Lead AI Engineer to define the technical backbone of our 2026 roadmap. As a pioneer in the industry, Nexus Horizon is committed to deploying cutting-edge Generative AI and scalable machine learning solutions that will redefine the landscape of enterprise technology. You won't just be maintaining systems; you will be building the infrastructure that will power the next decade of innovation.
Why Join Us?
- Work on high-impact projects that shape the 2026 AI landscape.
- Competitive compensation package with equity opportunities.
- Flexible remote-first culture with premium San Francisco office amenities.
- Access to state-of-the-art hardware and cloud resources.
Role Overview
In this pivotal role, you will lead a team of elite engineers to design, deploy, and optimize AI models that drive our core products. You will bridge the gap between theoretical research and production-grade engineering, ensuring our solutions are robust, scalable, and ethically sound.
Responsibilities
- Lead the architectural design and implementation of our 2026 strategic AI initiatives, including LLM integration and predictive analytics.
- Oversee the full machine learning lifecycle, from data ingestion and feature engineering to model training, validation, and deployment.
- Establish best practices for MLOps, ensuring high availability, security, and performance of production models.
- Mentor and develop a high-performing engineering team, fostering a culture of innovation and continuous learning.
- Collaborate cross-functionally with product managers and data scientists to translate business requirements into technical solutions.
- Monitor model performance in production and implement continuous improvement strategies to drive business metrics.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related technical field.
- 5+ years of experience in software engineering, with at least 3 years specializing in Machine Learning and Deep Learning.
- Strong proficiency in Python, PyTorch, TensorFlow, or similar frameworks.
- Proven experience deploying large-scale AI models in cloud environments (AWS, GCP, or Azure).
- Experience with vector databases and RAG (Retrieval-Augmented Generation) architectures.
- Excellent leadership skills with a track record of mentoring engineering teams.
- Demonstrated ability to work in a fast-paced, agile environment.