Job Description
At 2026 Innovations, we aren't just building software; we are architecting the future. We are seeking a visionary Senior Quantum AI Engineer to lead our research division in developing next-generation machine learning models that leverage the power of quantum computing. If you are passionate about pushing the boundaries of artificial intelligence and ready to define the technological landscape of 2026 and beyond, we want to hear from you.
As a key member of our elite R&D team, you will bridge the gap between theoretical quantum physics and practical, scalable AI applications. Join us in San Jose and help build the systems that will power the future economy.
Responsibilities
- Architect Design: Lead the architectural design and implementation of scalable, quantum-ready AI systems and deep learning frameworks.
- Research & Development: Conduct cutting-edge research in quantum machine learning algorithms, focusing on optimization, error correction, and data representation.
- Team Leadership: Mentor a team of junior engineers and data scientists, fostering a culture of innovation and technical excellence.
- Prototyping: Build rapid prototypes to validate new AI concepts and demonstrate feasibility for enterprise integration.
- Collaboration: Partner with cross-functional teams, including software engineers, product managers, and quantum physicists, to translate research into production-ready solutions.
- System Optimization: Continuously optimize AI models for speed, accuracy, and resource efficiency on hybrid quantum-classical hardware.
Qualifications
- Education: Master’s or PhD in Computer Science, Physics, Mathematics, or a related field with a focus on AI and Quantum Computing.
- Experience: Minimum of 5+ years of professional experience in machine learning, deep learning, or AI research, with at least 2 years working with quantum computing platforms (e.g., Qiskit, Cirq, Amazon Braket, or Azure Quantum).
- Technical Skills: Proficiency in Python, TensorFlow, PyTorch, and quantum computing libraries. Strong understanding of linear algebra, probability, and statistics.
- Cloud Proficiency: Experience deploying and managing AI workloads on major cloud platforms (AWS, Azure, or GCP).
- Communication: Excellent written and verbal communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
- Problem Solving: Demonstrated ability to solve complex, unstructured problems in high-pressure environments.