Principal MLOps Architect

With over 20 years of market experience, Northwind Robotics brings together technologists, creators, and innovators across Europe, North and Latin America, and the Middle East. Join our international team and help solve the advanced technology challenges of tomorrow. We are looking for an experienced and hands-on AI/ML Architect to drive the design, development, and operationalization of enterprise-scale AI systems across both research and production environments. This role combines deep expertise in Machine Learning, Generative AI, distributed data systems, and cloud-native architectures with strong technical leadership and strategic thinking. You will lead complex AI initiatives end-to-end — from early experimentation and research to scalable deployment in global enterprise environments. The ideal candidate is passionate about innovation, capable of operating at both strategic and hands-on levels, and experienced in leading cross-functional teams in highly dynamic environments. Responsibilities Lead the design and implementation of enterprise-scale AI/ML solutions across multiple business domains Drive adoption of Large Language Models (LLMs), Generative AI, NLP/NLU, and advanced analytics solutions Define AI architecture standards, MLOps best practices, and scalable deployment strategies Translate research initiatives into production-ready AI solutions Architect scalable distributed data-processing systems handling large-scale and real-time workloads Design and optimize cloud-native AI platforms using modern data engineering technologies Lead cloud migration and modernization initiatives across Azure and AWS environments Build and optimize data pipelines leveraging Spark, Databricks, Delta Lake, Kubernetes, and containerized environments Ensure reliability, scalability, observability, and cost-efficiency of AI infrastructure Design and implement enterprise-grade conversational AI and chatbot platforms Develop Retrieval-Augmented Generation (RAG), agentic workflows, and LLM orchestration systems Define governance, evaluation, monitoring, and responsible AI practices for GenAI systems Collaborate closely with research, engineering, and business teams to operationalize AI solutions securely and efficiently Lead and mentor distributed teams of data scientists, ML engineers, and software engineers Support AI innovation programs and enterprise AI adoption strategies Communicate complex technical concepts effectively to both technical and non-technical stakeholders Requirements Master’s or Ph.D. degree in Computer Science, Data Science, Machine Learning, or a related field 10+ years of experience in AI/ML, data science, distributed systems, or related engineering domains Proven experience designing and deploying enterprise-scale AI solutions in production environments Strong background in both research-oriented and industrial AI ecosystems Experience leading global or distributed technical teams Demonstrated success delivering AI transformation and modernization initiatives Technical Expertise Large Language Models (LLMs) Generative AI systems NLP / NLU Apache Spark Databricks Delta Lake Distributed computing architectures Streaming and batch processing pipelines SQL / NoSQL databases Azure and/or AWS Docker & Kubernetes CI/CD pipelines Infrastructure-as-Code MLOps frameworks Python and/or Scala Nice to Have Experience with AI governance and responsible AI practices Experience building AI platforms serving multiple teams or business units Experience optimizing cloud infrastructure and reducing operational costs Perks and Benefits: Flexible work schedule Fixed financial bonus issued upfront on a quarterly basis, covering the average market price of private medical care and sport card - B2B contract Present on the occasion of birthday, wedding, child birth E-learning accounts for Coursera, O'Relly, Udemy Corporate language school