Job Description
About TechNova Innovations
We are at the forefront of the technological singularity, building the systems that will define the year 2026. We are seeking a visionary Senior AI Architect to lead the development of our proprietary General Intelligence engine. You will bridge the gap between theoretical breakthroughs and scalable production systems, ensuring our AI not only understands the world but improves it.
Why Join Us?
Work on projects that have a tangible impact on global infrastructure. Enjoy a competitive salary, equity packages, and a culture that prioritizes innovation and ethical AI development.
Responsibilities
- Architectural Design: Design and implement scalable machine learning pipelines and AI architectures tailored for high-volume, low-latency data processing.
- Research Leadership: Lead research initiatives focused on Reinforcement Learning and Large Language Models (LLMs) to drive product innovation and competitive advantage.
- Collaboration: Collaborate with cross-functional teams (Data Science, Software Engineering, Product Management) to translate complex business needs into robust technical solutions.
- Ethics & Compliance: Ensure all AI systems adhere to strict ethical guidelines, bias mitigation standards, and regulatory compliance (GDPR/CCPA).
- Mentorship: Mentor junior engineers and conduct technical code reviews to maintain high engineering standards and foster a culture of continuous learning.
Qualifications
- Education: Ph.D. or Master’s degree in Computer Science, Mathematics, Statistics, or a related technical field.
- Experience: Minimum of 5+ years of experience in Machine Learning Engineering, AI Architecture, or Deep Learning Research.
- Technical Skills: Proficiency in Python, TensorFlow, PyTorch, and distributed computing frameworks (Kubernetes, AWS/GCP).
- Deployment: Proven track record of deploying production-ready AI models at scale with high availability.
- Domain Knowledge: Strong understanding of Natural Language Processing (NLP), Computer Vision, or Deep Reinforcement Learning.