Job Description
<p>Are you ready to define the future of Artificial Intelligence? Quantum Leap Technologies is seeking a visionary Senior AI Engineer to join our elite R&D team. We are not just building AI for today; we are architecting the intelligent systems that will dominate the landscape in <strong>2026 and beyond</strong>. If you thrive on complexity and are passionate about Generative AI, Large Language Models (LLMs), and ethical machine learning, this is your opportunity to lead the next technological revolution.</p>
<p>In this role, you will bridge the gap between theoretical research and production-grade deployment. You will work on cutting-edge projects involving autonomous agents, predictive analytics, and next-generation neural architectures. We offer a competitive package, remote-first flexibility, and the chance to work with industry pioneers.</p>
Responsibilities
- <ul>
- <li>Design, train, and deploy state-of-the-art machine learning models tailored for high-volume enterprise applications.</li>
- <li>Lead the architectural design of scalable AI infrastructure capable of handling petabyte-scale data processing in 2026 environments.</li>
- <li>Collaborate with cross-functional teams of data scientists, product managers, and engineers to integrate AI capabilities into core products.</li>
- <li>Research and implement novel algorithms to improve model accuracy, efficiency, and fairness.</li>
- <li>Mentor junior engineers and conduct code reviews to maintain high technical standards within the AI lab.</li>
- <li>Optimize existing models for edge devices and cloud environments to ensure low-latency performance.</li>
- </ul>
Qualifications
- <ul>
- <li>Ph.D. or Master’s degree in Computer Science, Machine Learning, or a related quantitative field.</li>
- <li>Minimum of 5 years of professional experience in AI/ML engineering, with a focus on Deep Learning and NLP.</li>
- <li>Expert proficiency in Python, PyTorch, TensorFlow, or JAX.</li>
- <li>Proven experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).</li>
- <li>Strong understanding of MLOps pipelines, version control (Git), and CI/CD practices.</li>
- <li>Excellent problem-solving skills and the ability to communicate complex technical concepts to non-technical stakeholders.</li>
- </ul>