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Build, train, and deploy ML/DL models (including computer vision) to solve business tasks, focusing on data prep, feature engineering, and production monitoring.
Design and deploy production-grade GenAI and ML solutions on AWS, optimizing cost, security, and performance while embedding reusable patterns into DoiT’s Cloud Intelligence platform.
Design and deploy production-grade GenAI and ML solutions on AWS for enterprise customers, focusing on cost efficiency, reliability, and security while creating reusable patterns and driving product adoption.
Мы ищем ML-инженера , который будет разрабатывать и внедрять модели машинного обучения для задач прогнозирования. Вы присоединитесь к команде, которая строит системы, помогающие бизнесу принимать решения на основе…
Build and improve NLP and Generative AI solutions using prompt engineering, fine-tuning, and RAG; evaluate models and datasets.
Build and improve NLP and Generative AI solutions using prompt engineering, fine-tuning, RAG, and vector databases in Python with PyTorch and HuggingFace.
Build and improve NLP and Generative AI solutions using prompt engineering, fine-tuning, RAG, and evaluation frameworks while collaborating with AI Engineering teams.
Build and tune NLP and generative-AI models using prompt engineering, fine-tuning, RAG, and vector databases, then deploy them with Docker and GPU training.
Design and deploy scalable, real-time AI systems including LLM inference pipelines, RAG, and vector databases using Python, TensorFlow/PyTorch, and Kubernetes.
Build and deploy AI-powered cybersecurity agents that autonomously investigate threats using LLMs, tool-calling workflows, and evaluation frameworks.
Build and maintain data pipelines and cross-platform ML models using TensorFlow and PyTorch to process public and customer data for AI training and backend integration.
Lead advanced analytics projects, mentor junior engineers, and build predictive models using Python, SQL, and SPSS for UK government clients.
Design and maintain CI/CD, IaC, and MLOps pipelines on AWS/Azure/GCP, focusing on Kubernetes, observability, and AI model deployments while enforcing DevSecOps practices.
Designs and maintains CI/CD pipelines, Kubernetes clusters, and cloud infrastructure for ML and general apps, automating deployments and monitoring systems.
Build and deploy AI solutions (LLMs, RAG, ML) to optimize Safran Aircraft Engines’ customer support and service operations, translating business needs into robust, explainable models.
Build and deploy AI solutions (LLMs, RAG, ML) to improve customer support and service operations, translating business needs into robust, explainable models and driving adoption across teams.
Build and maintain NLP pipelines to enrich patient data, validate results, and ensure data governance in a healthcare data warehouse using Python/R and ML frameworks like PyTorch/Transformers.
Build and maintain a healthcare data platform, using NLP and ML to extract, validate, and document unstructured patient data while ensuring compliance and quality.
Build and optimize NLP pipelines to extract, validate, and document unstructured patient data for a healthcare data warehouse, using Python/R and ML libraries like PyTorch.
Design scalable data architectures and MLOps pipelines, industrialize ML models, and ensure data quality for enterprise AI projects in cloud environments.
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