Design end-to-end AI/ML architectures: ingestion, training, deployment, monitoring.
Lead evaluation and selection of AI/ML tools, frameworks, and cloud components.
Define governance and standards for responsible AI; shape long-term AI roadmap.
Guide the full ML lifecycle: data prep, modeling, experimentation, deployment.
Oversee technical design and ensure quality, reliability, and security; mentor engineers.

🎯 Requirements

7+ years in data science, ML, or AI engineering
3+ years in senior or principal architectural role
Python and ML frameworks: TensorFlow, PyTorch, Scikit-Learn
Cloud AI services: AWS Sagemaker, Azure ML, GCP Vertex AI
Data engineering tools: Spark, Databricks, Airflow, Kafka
LLM architectures, fine-tuning, embeddings, vector stores (FAISS, Pinecone, Weaviate)

🎁 Benefits

Close cooperation with a customer
Challenging tasks
Competence development
Team of professionals
Dynamic environment with a low level of bureaucracy

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