AI Architect
RandomTrees
- Communication: Excellent verbal and written communication, with the ability to explain complex concepts simply and influence decisions.
- Architecture: Proven experience designing complex, distributed AI/ML systems and platforms end to end.
- AI/ML expertise: Strong grounding in machine learning, deep learning, and (ideally) GenAI/LLMs, including RAG and fine-tuning.
- MLOps: Hands-on experience with tools such as MLflow, Kubeflow, Airflow, SageMaker, Vertex AI, Azure ML, or Databricks.
- Engineering: Strong programming skills (Python required), plus experience with Docker, Kubernetes, and microservices/API design.
- Cloud and data: Experience with AWS, Azure, or GCP, and with big data technologies (Spark, Kafka, data lakes/warehouses).
- Stakeholder management: A track record of working with senior stakeholders, managing expectations, and delivering across teams. xhyhwjd
- Resilience: Comfortable with ambiguity, tight timelines, and challenging technical environments.
Vacancy posted 1 day ago
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