Job Description
We are seeking a visionary Senior AI Architect to lead the technical evolution of our flagship initiative, Project 2026. In this role, you will be at the forefront of defining how artificial intelligence will reshape industries in the coming decade. You won't just be building models; you will be architecting the intelligence layer of our next-generation platform.
Why Join Nexus Horizon Labs?
Our team is dedicated to pushing the boundaries of what is possible. You will have the autonomy to experiment with novel architectures and the responsibility to deliver robust, scalable solutions that stand the test of time. We offer a dynamic environment where innovation is rewarded and career growth is limitless.
Benefits & Perks
- Competitive salary ($180k - $250k)
- Comprehensive health, dental, and vision insurance.
- Unlimited PTO and flexible working hours.
- Stock options in a rapidly growing startup.
Responsibilities
- Architect and implement scalable machine learning pipelines for the Project 2026 initiative.
- Collaborate with cross-functional teams to define data requirements and model accuracy benchmarks.
- Optimize existing algorithms to reduce latency and improve inference speeds for real-time applications.
- Conduct code reviews and mentor junior engineers on best practices in AI/ML engineering.
- Stay abreast of cutting-edge research in generative AI and large language models to integrate into the 2026 roadmap.
- Deploy models to production environments using containerization and orchestration tools.
Qualifications
- Master’s degree in Computer Science, Data Science, or a related technical field (PhD preferred).
- Minimum of 6 years of professional experience in AI/ML engineering.
- Proficiency in Python and deep frameworks such as PyTorch or TensorFlow.
- Strong understanding of distributed systems, microservices architecture, and cloud platforms (AWS/GCP/Azure).
- Experience with MLOps tools (MLflow, Kubeflow) and version control (Git).
- Demonstrated ability to solve complex mathematical problems and optimize code for performance.