Job Description
The Opportunity: Nexus Future Labs is pioneering the next generation of artificial intelligence. We are looking for a visionary Senior AI Engineer to lead the architecture and development of our Project 2026 initiative—a transformative roadmap designed to redefine human-machine interaction by 2026.
As a key member of our elite AI division, you will not just implement existing models; you will architect the infrastructure for tomorrow. If you are passionate about pushing the boundaries of generative AI, large language models, and autonomous systems, this is your chance to build the future.
Why Join Us?
- Work on cutting-edge technology with a team of industry pioneers.
- Competitive equity and compensation packages.
- Flexible remote-first culture with premium office amenities in San Francisco.
Key Responsibilities:
Responsibilities
- Architect AI Solutions: Design and deploy scalable, fault-tolerant machine learning pipelines and neural network architectures for Project 2026.
- Model Optimization: Lead research into model compression, quantization, and latency reduction to ensure real-time performance.
- Technical Leadership: Mentor junior engineers and data scientists, conducting code reviews and establishing best practices for MLOps.
- R&D Strategy: Collaborate with product managers to translate business requirements into advanced technical roadmaps.
- System Integration: Integrate AI models into complex enterprise ecosystems and ensure seamless data flow.
- Innovation: Stay ahead of the curve on emerging AI trends, including reinforcement learning and multi-modal learning.
Qualifications:
Qualifications
- Education: Master’s or Ph.D. in Computer Science, Mathematics, or a related field.
- Experience: 5+ years of professional experience in machine learning engineering or applied AI research.
- Programming: Proficiency in Python, C++, and deep learning frameworks (PyTorch or TensorFlow).
- Cloud Mastery: Extensive experience deploying models on AWS, GCP, or Azure using Kubernetes and Docker.
- Mathematics: Strong foundation in linear algebra, calculus, and probability/statistics.
- Communication: Excellent ability to communicate complex technical concepts to non-technical stakeholders.
Skills: Python, PyTorch, TensorFlow, AWS, Kubernetes, MLOps, NLP, Computer Vision, Deep Learning, Docker, SQL, Agile Methodologies.