Job Description
We are seeking a visionary Senior AI Engineer to join our elite team in San Francisco. As we architect the technological landscape for the 2026 era, you will be responsible for developing cutting-edge machine learning models and scalable AI infrastructure. This is a rare opportunity to shape the future of intelligent automation and drive innovation in a high-growth environment.
Why Join Nexus Horizon Labs?
- Future-Ready Tech Stack: Work with the latest in Generative AI, LLMs, and Quantum-ready algorithms.
- Premium Compensation: Competitive base salary and equity package.
- Flexible Environment: Hybrid work model supporting top-tier talent from anywhere in the US.
Your Mission:
You will lead the design and implementation of robust AI systems that power our core products. You will bridge the gap between theoretical research and production-grade engineering, ensuring our solutions are scalable, secure, and efficient.
Responsibilities
- Lead Model Development: Design, train, and fine-tune large-scale machine learning models, focusing on Generative AI and NLP.
- Infrastructure Engineering: Build and maintain scalable MLOps pipelines using Kubernetes, Docker, and cloud-native services (AWS/GCP).
- Performance Optimization: Conduct rigorous testing to optimize model inference latency and cost-efficiency.
- Cross-Functional Collaboration: Partner with product managers and data scientists to define technical requirements and roadmap strategies.
- Code Review & Mentorship: Mentor junior engineers, conduct code reviews, and establish best practices for AI engineering within the organization.
- Research & Innovation: Stay ahead of industry trends to integrate emerging technologies (e.g., Transformers, Reinforcement Learning) into our stack.
Qualifications
- Education: Bachelor’s degree in Computer Science, Mathematics, or a related field; Master’s degree preferred.
- Experience: 5+ years of professional experience in software engineering, with at least 3 years specifically in AI/ML development.
- Programming: Proficiency in Python, PyTorch, TensorFlow, or Scikit-learn.
- System Design: Strong understanding of distributed systems, API design, and database architecture.
- Communication: Excellent written and verbal communication skills with the ability to explain complex technical concepts to non-technical stakeholders.
- Tools: Experience with version control (Git), CI/CD pipelines, and cloud platforms (AWS/Azure/GCP).