Principal MLOps Architect
With over 20 years of market experience, Intellias 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
Principal MLOps Architect
Principal MLOps Architect