eleks - AI/ML Architect
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Requirements
• 7+ years of experience in data science, machine learning, or AI engineering • 3+ years in a senior or principal-level architectural role • Strong proficiency in Python and common ML/AI frameworks (TensorFlow, PyTorch, Scikit-Learn, transformers libraries) • Hands-on experience with: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)MLOps tools (MLflow, Kubeflow, DVC, CI/CD pipelines) • Solid understanding of distributed computing, APIs, microservices, and containerization (Docker, Kubernetes). • ## PERSONAL CHARACTERISTICS • Strong communication skills and ability to translate complex technical concepts for non-technical audiences • Strategic mindset with experience influencing product and technical decisions • Ability to lead, mentor, and partner effectively across teams • Passion for innovation, experimentation, and continuous improvement
Responsibilities
• Architecture & Strategy • Design end-to-end AI/ML architectures, including data ingestion pipelines, feature stores, model training, deployment patterns, and monitoring frameworks • Lead the evaluation and selection of AI/ML tools, frameworks, cloud components, and platforms • Define standards, best practices, and governance frameworks for responsible AI usage • Partner with product and engineering leadership to shape the long-term AI roadmap • Technical Leadership • Provide expert guidance across the full ML lifecycle: data preparation, modeling, experimentation, optimization, deployment, monitoring • Architect scalable solutions using Python-based ML stacks (e.g., TensorFlow, PyTorch, Scikit-Learn) and modern cloud environments (AWS, Azure, GCP).Support the development of LLM-based applications, vector database architectures, and retrieval-augmented generation (RAG) systems • Evaluate new AI capabilities (e.g., agent frameworks, fine-tuning strategies, MLOps automation) • Execution & Delivery • Oversee the technical design of AI projects and ensure solution quality, reliability, and security • Work with cross-functional teams to define clear success metrics for AI initiatives • Conduct architecture reviews, code reviews, and technical deep dives • Mentor engineers and data scientists to elevate technical excellence. • Close cooperation with a customer • Competence development • Team of professionals • Dynamic environment with a low level of bureaucracy
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