Job Description
We are seeking a visionary Lead AI Engineer to spearhead our Project 2026 initiative. This is not just a job; it is an opportunity to architect the future of human-machine interaction and redefine the technological landscape by 2026. We are building the infrastructure for an autonomous, intelligent world, and we need a pioneer to lead our core R&D division.
In this pivotal role, you will bridge the gap between theoretical machine learning and production-grade systems. You will define the architectural vision for our next-generation neural networks and mentor a team of world-class data scientists. If you are driven by the challenge of solving complex problems at scale and are ready to shape the technology of tomorrow, we want to meet you.
Responsibilities
- Architectural Leadership: Design and implement scalable, high-performance AI infrastructure capable of processing petabytes of data in real-time.
- Research & Development: Drive innovation in Deep Learning and Reinforcement Learning, specifically targeting breakthroughs relevant to the 2026 roadmap.
- Model Deployment: Oversee the transition from prototype to production, ensuring models are robust, efficient, and ethically aligned.
- Team Mentorship: Cultivate a high-performance culture by mentoring junior engineers and conducting technical workshops.
- Strategic Planning: Collaborate with product leadership to align AI capabilities with business goals and market trends.
- System Optimization: Continuously optimize existing models to reduce latency and improve inference accuracy.
Qualifications
- Education: Ph.D. or Master’s degree in Computer Science, Artificial Intelligence, or a related quantitative field.
- Experience: 8+ years of experience in software engineering, with at least 5 years focused on machine learning and AI systems.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, and distributed computing frameworks (e.g., Kubernetes, Spark).
- Domain Knowledge: Deep understanding of NLP, Computer Vision, or Generative AI models.
- Leadership: Proven ability to lead cross-functional teams and manage large-scale technical projects.
- Problem Solving: Exceptional analytical skills with a track record of solving ambiguous, high-impact problems.