Urgent Architect
3 weeks ago
We're looking for someone who not only enjoys writing code and seeing their ideas come to fruition on a global scale, but is also able to upskill the engineers around them through leading by example. In this role, you will be leading the development of cloud native capabilities to ensure our Data Scientists can focus on model development and delivering cutting edge intelligent solutions.
What You'll do:
- Drive and own the delivery of AI platforms from design and architecture to production
- Leverage your deep knowledge of AI engineering to build Wayfair's next generation AI capabilities
- Design scalable systems using Python, Go, Kubernetes, GCP, Airflow, and other technologies to support AI workloads
- Think outside of the current technology/stack limitations to push the boundaries on what is possible with AI and deliver feasible solutions collaboratively
- Champion open source solutions and Google Cloud native technologies, and their application to our AI use cases
- Develop end to end AI solutions that can power the full range of AI initiatives at Wayfair
- Partner with product leaders to understand technical pain points for data scientists and other teams building AI applications and translate them into clear and robust platform solutions
- Advise engineering and product management on AI platform technical roadmap, ensuring that the vision aligns with broader company objectives
- Promote a culture of engineering excellence and strengthen the technical expertise of our AI engineering and product teams
- Keep current on AI engineering technology trends, evaluate, work on proof-of-concept and make recommendations on the technologies based on their merit
Who you are:
- 10+ years of experience in software engineering and designing systems at scale
- 4+ years of experience in Linux-based development, Python/Go development, and leading engineering teams
- Experience developing AI/ML pipelines, model deployment systems, and orchestrating AI workloads with Kubernetes
- Strong understanding of containerization, AI system scalability challenges, and software engineering best practices
- Experience with AI/ML frameworks (TensorFlow, PyTorch) and model serving technologies
- Knowledge of AI system monitoring, performance optimization, and model lifecycle management
- Excellent communication skills with demonstrated experience driving teams and influencing technical decisions aligned with company AI strategy
- Hands-on experience in high-growth environments at scale, with ability to mentor engineers and collaborate with AI researchers and data scientists
Nice to Have:
- Mix of start-up and large-company experience working on AI solutions
- Familiarity with AI platforms (opensource or offered by Google Cloud) and how to implement them on a large scale
- Knowledge of vector databases, embedding systems, or real-time AI inference optimization
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