Job Description
Shape the Future of Intelligence
Nexus Horizon AI is pioneering the next generation of artificial intelligence, with a strategic roadmap extending through 2026 and beyond. We are seeking a visionary Senior AI Architect to lead the design and deployment of our proprietary generative models. In this pivotal role, you will bridge the gap between theoretical machine learning research and scalable, production-grade engineering, ensuring our systems are robust, ethical, and ready for the demands of a rapidly evolving digital landscape.
Why Join Us?
- Work at the forefront of AI development with a focus on long-term scalability and ethical AI.
- Competitive compensation package including equity and performance bonuses.
- Flexible remote-first culture with a vibrant hub in San Francisco.
Key Responsibilities
- Architect Scalable LLM Pipelines: Design and implement robust, high-throughput infrastructure for Large Language Models and multimodal systems.
- Optimization & Efficiency: Drive model compression and optimization techniques to reduce inference costs and latency.
- Ethical AI Governance: Establish frameworks for bias mitigation, data privacy, and responsible AI deployment.
- Technical Leadership: Mentor a team of data scientists and engineers, providing architectural guidance and best practices.
- Research Integration: Translate cutting-edge academic research into practical, production-ready software solutions.
Qualifications
- Education: Master’s or PhD in Computer Science, Mathematics, or a related technical field.
- Experience: 7+ years of experience in machine learning engineering, with at least 3 years in a senior architectural or lead role.
- Technical Skills: Deep expertise in PyTorch, TensorFlow, or JAX; proven experience with transformer architectures and NLP.
- Infrastructure: Strong background in cloud-native architectures (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
- Problem Solving: Demonstrated ability to solve complex engineering problems and optimize large-scale data systems.
Responsibilities
- Design and oversee the implementation of complex AI model architectures.
- Collaborate with product and engineering teams to define AI capabilities.
- Monitor system performance and implement real-time monitoring solutions.
- Conduct code reviews and technical due diligence for third-party integrations.
Qualifications
- PhD or Master’s degree in a quantitative field.
- Extensive experience with deep learning frameworks.
- Strong proficiency in Python and distributed computing.
- Experience with MLOps tools (MLflow, Airflow).
- Excellent communication and leadership skills.