Job Description
We are seeking a visionary Senior AI Architect (2026 Vision) to lead our next-generation autonomous systems division. In this pivotal role, you will define the technical roadmap for AI integration, ensuring our solutions remain at the cutting edge of technology by 2026 and beyond. You will bridge the gap between theoretical research and scalable production engineering, mentoring a team of elite engineers and data scientists.
Join a company that isn't just adapting to the future; we are building it. We offer competitive compensation, comprehensive benefits, and the opportunity to work on projects that will define the era of Artificial General Intelligence.
Responsibilities
- Architectural Leadership: Design and implement scalable, fault-tolerant AI infrastructure and machine learning pipelines for large-scale applications.
- Strategic Roadmapping: Define the technical vision and 2026 roadmap for AI capabilities, identifying emerging technologies (e.g., LLMs, Quantum-ready algorithms) to integrate into our core product.
- Team Mentorship: Guide a high-performing engineering team in best practices for MLOps, model training, and deployment.
- Performance Optimization: Drive initiatives to reduce inference latency and improve model accuracy across distributed systems.
- Collaboration: Partner with product managers and stakeholders to translate complex technical requirements into feasible engineering solutions.
- R&D: Spearhead proof-of-concept projects exploring novel AI architectures and generative AI applications.
Qualifications
- Education: Master’s or PhD in Computer Science, Mathematics, or a related technical field from a top-tier university.
- Experience: 8+ years of experience in software engineering and machine learning, with at least 3 years in a senior or leadership role.
- Technical Skills: Deep expertise in Python, PyTorch, TensorFlow, or JAX. Strong knowledge of distributed computing systems (Kubernetes, Docker) and MLOps platforms.
- AI Specialization: Proven track record in Natural Language Processing (NLP), Computer Vision, or Reinforcement Learning.
- Problem Solving: Demonstrated ability to solve complex, ambiguous problems and make data-driven architectural decisions.
- Communication: Exceptional verbal and written communication skills, capable of explaining complex technical concepts to non-technical stakeholders.