Job Description
Are you ready to architect the future of AI?
QuantumLeap Technologies is seeking a visionary Senior AI Research Engineer to spearhead our Project 2026 initiative. As we push the boundaries of generative intelligence and autonomous systems, we need a technical leader who can bridge the gap between theoretical research and scalable production infrastructure. This is a unique opportunity to define the roadmap for AI adoption by 2026 and beyond.
In this role, you will work at the intersection of deep learning, cognitive architecture, and high-performance computing. You will lead a team of top-tier researchers to build models that not only understand context but also reason and adapt in real-time environments.
Responsibilities
- Lead the strategic research and development of core AI models for the Project 2026 initiative, ensuring alignment with long-term product goals.
- Architect and optimize deep learning pipelines, focusing on scalability, latency, and energy efficiency for edge and cloud deployment.
- Collaborate with cross-functional teams of product managers, engineers, and designers to translate research breakthroughs into user-centric features.
- Mentor junior researchers and engineers, fostering a culture of innovation, technical excellence, and continuous learning.
- Stay at the forefront of the industry by monitoring emerging trends in Large Language Models (LLMs) and multimodal AI.
- Drive the implementation of rigorous testing and evaluation frameworks to ensure model robustness and safety.
Qualifications
- PhD or Master’s degree in Computer Science, Mathematics, or a related technical field with a focus on AI/ML.
- Minimum of 5+ years of experience in AI research, machine learning engineering, or a related role.
- Expert proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow.
- Proven track record of publishing in top-tier conferences (NeurIPS, ICML, ACL) or shipping impactful AI products at scale.
- Strong understanding of distributed systems, cloud infrastructure (AWS/Azure/GCP), and MLOps practices.
- Excellent problem-solving skills and the ability to thrive in a fast-paced, high-ambiguity environment.