Role Focus: Build and deploy production-grade AI/ML and Generative AI systems, with a focus on LLMs, RAG, personalization, MLOps, and cloud infrastructure. - Build RAG pipelines, semantic/vector search, conversational AI, and intelligent assistants.
Задачи:
— Build RAG pipelines, semantic/vector search, conversational AI, and intelligent assistants.
— Develop recommendation, ranking, classification, and predictive ML models.
— Own end-to-end ML pipelines from data processing and training to deployment and monitoring.
— Build MLOps / GenAIOps workflows, CI/CD, GPU inference, and cloud-native AI infrastructure.
— Work with Product and Engineering to measure business impact through KPIs and experiments.
— Improve AI system scalability, reliability, cost, governance, and performance.
Требования:
— 4–5+ years in AI, ML, or Data Science.
— Strong Python, SQL, and production ML experience.
— Hands-on experience with LLMs, Transformers, embeddings, RAG, and prompt engineering.
— Experience with PyTorch/TensorFlow, Hugging Face, LangChain/LlamaIndex.
— Strong knowledge of Docker, Kubernetes, MLflow/W&B, CI/CD, AWS, and Terraform.
— Experience with Kafka, ETL pipelines, vector databases, and search systems.
— Ability to independently take AI projects from idea to production.
Плюсы:
— Experience with A/B testing, responsible AI, recommendation systems, regulated environments, or team leadership.
— Candidate should be able to work on US time schedule.
— Good English conversation skill is much much preferred.
Контакты работодателя доступны по кнопке «Откликнуться» после входа.
65/100
Средняя вакансия
Оценка от Job Hunters AI
Senior AI / Machine Learning Engineer (Generative AI & LLMs); компания не названа; зарплата не указана; понятные задачи; современный стек; гибкий формат.
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