Job Description
Shape the Future with 2026
We are seeking a visionary Senior AI Architect to lead our next generation of artificial intelligence initiatives. At 2026, we don't just predict the future; we engineer it. Join a team of elite engineers and data scientists dedicated to building scalable, ethical, and transformative AI systems that redefine industry standards.
Why Join Us?
- Impactful Work: Deploy models that directly influence millions of users worldwide.
- Innovation First: Work with the latest tech stack, including LLMs, Transformers, and Edge AI.
- Competitive Compensation: Top-tier salary and equity packages for top talent.
- Culture of Excellence: A remote-first, inclusive environment that values deep work and continuous learning.
The Role
You will be responsible for designing the overarching architecture for our machine learning platforms. You will bridge the gap between theoretical research and production-grade engineering, ensuring our systems are robust, secure, and efficient at scale.
Responsibilities
- Architect Design: Design and implement scalable, distributed AI systems and microservices architecture.
- Model Lifecycle: Oversee the full ML lifecycle, from data ingestion and preprocessing to model training, evaluation, and deployment (MLOps).
- Team Leadership: Mentor junior engineers and data scientists, conducting code reviews and architectural reviews to ensure best practices.
- Research & Dev: Stay at the forefront of AI research, evaluating new algorithms and frameworks to integrate into our product stack.
- Performance Optimization: Continuously monitor system performance, optimizing latency, throughput, and resource utilization.
- Collaboration: Partner with product managers and stakeholders to define technical requirements and roadmaps.
Qualifications
- Experience: 7+ years of experience in software engineering and 3+ years specifically in Machine Learning Engineering or AI Architecture.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, or JAX. Deep understanding of distributed systems, SQL, and NoSQL databases.
- Cloud Expertise: Strong experience deploying models on AWS, GCP, or Azure using containerization (Docker/Kubernetes).
- Education: MS or PhD in Computer Science, Mathematics, or a related technical field (or equivalent practical experience).
- Problem Solving: Ability to tackle complex, ambiguous problems with creative, data-driven solutions.
- Communication: Excellent verbal and written communication skills for cross-functional collaboration.