Job Description
Shape the Future of Intelligence at 2026 Technologies
2026 Technologies is pioneering the next generation of artificial intelligence. We are looking for a Senior AI Architect to lead the development of scalable machine learning systems and drive innovation in predictive analytics. If you are passionate about pushing the boundaries of what AI can achieve, this is your opportunity to join a world-class team.
What You Will Do:
- Design and implement cutting-edge deep learning architectures for enterprise solutions.
- Lead the end-to-end development of AI models from research to production deployment.
- Collaborate with cross-functional teams to integrate AI capabilities into our core products.
- Mentor junior engineers and data scientists, fostering a culture of technical excellence.
- Optimize cloud infrastructure (AWS/GCP) for maximum performance and cost efficiency.
Why Apply:
- Competitive salary ($180k - $250k USD).
- Equity package and performance bonuses.
- Comprehensive health benefits and flexible remote work options.
Responsibilities
- System Architecture: Design robust, scalable, and secure AI infrastructure to handle large-scale data processing and real-time inference.
- Model Optimization: Fine-tune existing models and develop new ones using Python, TensorFlow, and PyTorch to improve accuracy and speed.
- Technical Leadership: Provide technical guidance and mentorship to the engineering team, conducting code reviews and architectural planning.
- Research & Development: Stay abreast of the latest advancements in AI and implement novel techniques to solve complex business problems.
- Deployment: Manage the CI/CD pipeline for machine learning models, ensuring seamless deployment and monitoring.
- Stakeholder Communication: Translate complex technical concepts into actionable insights for non-technical stakeholders.
Qualifications
- Education: Master’s or PhD in Computer Science, Mathematics, or a related field.
- Experience: Minimum of 5 years of professional experience in software engineering and machine learning.
- Technical Proficiency: Strong command of Python, C++, or Java; expertise in frameworks like TensorFlow, PyTorch, or Keras.
- Cloud Computing: Proven experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
- Data Engineering: Experience with big data technologies (Spark, Hadoop) and SQL databases.
- Problem Solving: Demonstrated ability to troubleshoot complex technical issues and deliver high-quality solutions under pressure.
- Communication: Excellent verbal and written communication skills.