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Роль чётко описана как senior-позиция по созданию AI-решений, включая agentic AI и полный цикл от экспериментов до production; основные компромиссы - работа только из офиса и отсутствие данных о зарплате.
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Описание вакансии
Текст:
Hirify AI/Оригинал
TL;DR
Data Scientist – Agentic AI (Generative AI/LLMs): Designing and deploying machine learning, generative AI, and agentic AI solutions for complex enterprise challenges with an accent on LLM applications, retrieval-augmented generation, intelligent agents, and responsible AI. Focus on building multi-agent workflows, evaluating model and agent reliability, and taking AI systems from experimentation through production with MLOps, LLMOps, and AgentOps practices.
Location: In person in Madrid, Barcelona, or Granada, Spain
Company
hirify.global runs and reimagines mission-critical technology systems for leading businesses, using AI-powered insight to enable smarter decisions and innovation.
What you will do
Translate client and business needs into machine learning, generative AI, and agentic AI solutions.
Design and develop LLM applications using embeddings, retrieval-augmented generation, prompt engineering, and model adaptation.
Build, train, evaluate, deploy, and monitor predictive, analytical, deep learning, and agentic AI systems.
Develop intelligent agents and multi-agent systems that reason, plan, use tools and enterprise systems, and execute complex workflows with human oversight.
Establish evaluation, observability, MLOps, LLMOps, and AgentOps practices for reliable, scalable, and maintainable AI solutions.
Collaborate with architects, engineers, domain experts, clients, and stakeholders while contributing technical leadership and supporting junior practitioners.
Requirements
Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Mathematics, Statistics, Engineering, or a related technical field, combined with solid professional experience in Data Science, Machine Learning, or AI development.
Proven experience designing, developing, and evaluating machine learning models, including statistical methods, supervised and unsupervised learning, and deep learning.
Hands-on experience with large language models, prompt engineering, embeddings, retrieval-augmented generation, and their capabilities, limitations, and evaluation.
Practical knowledge of AI agents and agentic architectures, including tool integration, orchestration, reasoning workflows, and agentic development frameworks.
Strong proficiency in Python and relevant Data Science and AI libraries such as Scikit-learn, PyTorch, TensorFlow, Hugging Face, or equivalent technologies.
Experience across data preparation, experimentation, model evaluation, deployment, and monitoring, with familiarity with MLOps, LLMOps, and AgentOps.
Strong analytical and problem-solving skills, including translating business challenges into technical AI solutions.
Ability to work independently and collaboratively in multidisciplinary teams and communicate technical concepts effectively with business and technical stakeholders.
Nice to have
Experience with complex agentic workflows or multi-agent systems using LangGraph, AutoGen, CrewAI, or equivalent technologies.
Familiarity with agent observability, tracing, evaluation frameworks, LLM-as-a-Judge approaches, and tools such as Langfuse, LangSmith, RAGAS, or DeepEval.
Experience with LLM fine-tuning, model optimization, advanced RAG architectures, or open-source foundation models.
Experience with Azure AI, AWS, or Google Cloud AI/ML services and relevant certifications.
Experience deploying enterprise AI applications using APIs, containerization, microservices, CI/CD pipelines, and scalable architectures.
Knowledge of AI governance, model explainability, security, privacy, and responsible AI practices.
Experience with enterprise AI projects, digital transformation, automation, or AI-powered business solutions.
Master’s degree, PhD, scientific publications, open-source contributions, or active participation in technical and research communities.
Culture & Benefits
In-person work in Spain with a supportive, inclusive culture focused on belonging, empathy, and shared success.
Be Well programs supporting financial, mental, physical, and social health.
Career development through personalized goals, continuous feedback, coaching, hands-on experience, and learning opportunities.
Access to certifications and training involving Microsoft, Google, and Amazon technologies.
Hiring process
If applying through an employee referral, select “Employee Referral” for “How Did You Hear About Us” and enter the referring contact’s hirify.global email address.
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