Job Description
Are you ready to define the future of technology? Quantum 2026 Labs is seeking a visionary Senior AI Architect to spearhead our next-generation neural network initiatives.
We are building the foundational infrastructure for the year 2026 and beyond, focusing on autonomous systems, predictive deep learning, and quantum-ready algorithms. If you have a passion for pushing the boundaries of machine learning and leading high-impact engineering teams, we want to hear from you.
Why Join Us?
- Work on cutting-edge technology that will shape the future.
- Competitive compensation and equity package.
- Flexible remote-first policy with a San Francisco hub.
The Role
As a Senior AI Architect, you will be responsible for designing, developing, and deploying scalable machine learning models that power our core products. You will collaborate with cross-functional teams to integrate AI solutions into our ecosystem, ensuring high performance and ethical AI standards.
Responsibilities
- Design & Development: Architect and implement scalable AI and machine learning systems using Python, TensorFlow, and PyTorch.
- Research Leadership: Lead research initiatives to explore new frontiers in neural networks and generative AI models.
- System Optimization: Oversee the deployment of models into production environments, ensuring low latency and high availability.
- Team Mentorship: Mentor junior engineers and data scientists, fostering a culture of innovation and continuous learning.
- Strategic Planning: Define technical roadmaps for AI infrastructure aligned with the company's 2026 vision.
- Collaboration: Work closely with product managers and stakeholders to translate business requirements into technical solutions.
Qualifications
- Education: Master’s or PhD in Computer Science, Machine Learning, or a related quantitative field.
- Experience: 7+ years of experience in software engineering, with at least 4 years specifically in AI/ML architecture.
- Technical Skills: Deep proficiency in Python, SQL, and cloud platforms (AWS, GCP, or Azure).
- Frameworks: Strong experience with ML frameworks such as PyTorch, TensorFlow, or JAX.
- Communication: Exceptional ability to communicate complex technical concepts to non-technical stakeholders.
- Problem Solving: Proven track record of solving complex engineering problems and optimizing large-scale systems.