Job Description
We are seeking a visionary Principal AI Engineer to define the technological roadmap for our 2026 initiatives. This is not a typical engineering role; it is an opportunity to architect the future of human-machine interaction. We are building the systems that will define the next decade of enterprise intelligence, and we need a leader who can bridge the gap between theoretical innovation and practical application.
As part of our elite engineering team, you will work on cutting-edge projects involving Generative AI, predictive analytics, and autonomous systems. If you are passionate about solving complex problems and shaping the future of technology, we want to hear from you.
Responsibilities
- Architect Future-Proof AI Systems: Design and deploy scalable machine learning models capable of handling next-generation data streams and real-time decision-making.
- Lead the 2026 Roadmap: Translate abstract future concepts into concrete technical specifications and implementation strategies for the coming years.
- Advanced NLP & Vision: Spearhead research into Natural Language Processing and Computer Vision to enhance our product suite and user experience.
- Code Review & Mentorship: Provide technical leadership, conduct rigorous code reviews, and mentor junior engineers to maintain high engineering standards.
- Collaborate with Cross-Functional Teams: Partner with product managers, data scientists, and designers to deliver end-to-end AI solutions.
- Optimize Infrastructure: Ensure AI models run efficiently on cloud infrastructure, focusing on latency, throughput, and cost optimization.
Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or a related field; PhD is a plus.
- Experience: 10+ years of experience in software engineering and machine learning, with at least 5 years in a lead or principal engineering role.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, and experience with MLOps tools (Kubeflow, MLflow).
- Frameworks: Deep understanding of deep learning architectures, transformers, and neural networks.
- Cloud Expertise: Strong experience deploying models on AWS, GCP, or Azure.
- Soft Skills: Exceptional problem-solving abilities, strong communication skills, and the ability to thrive in a fast-paced, innovative environment.