Tech Lead ML/AI Engineering

Description

Job Summary: Tech Lead ML/AI Engineering to technically lead the design and end-to-end implementation of ML/AI solutions, defining architectures and pipelines while ensuring engineering best practices. Key Highlights: 1. Lead the design and end-to-end implementation of ML/AI solutions 2. Define ML, CV, and Generative AI architectures and pipelines 3. Promote component reuse and technical mentoring **About the team** As a **Tech Lead ML/AI Engineering**, you will join our Data \& AI team, where data drives decisions. Specializing in comprehensive data assessments, this team ensures unparalleled data governance, compliance, and quality. Our team maps the entire cloud data journey—from raw information to actionable insights—creating customized data products. With AI solutions spanning business insights to forecasting, and expertise in cloud management, we ensure enterprises fully harness the potential of their data. **About the role** * Technically lead the design and implementation of end-to-end ML/AI solutions—from problem definition through deployment and production monitoring * Define Machine Learning, Computer Vision, and Generative AI architectures and pipelines, including RAG, embeddings, and agentic systems * Hands-on contribution to model development, feature engineering, training, validation, and inference services * Ensure engineering best practices—including model versioning, experiment tracking, MLOps/LLMOps, CI/CD, and observability * Collaborate closely with Data Engineers, MLOps, Product, and business stakeholders to ensure technical and functional alignment * Support pre-sales contexts and solution definition, contributing to technical proposals and estimations * Promote component reuse, accelerator creation, and technical mentoring of teams **What skills are we looking for?** * Proven experience in production ML/AI projects * Strong proficiency in Python and the Machine Learning and Deep Learning ecosystem * Practical experience with Generative AI, LLMs, RAG, and agent-based pipelines * Knowledge of API development, distributed systems, and cloud deployment * Experience with MLOps/LLMOps practices and model lifecycle management * Technical leadership ability, architectural thinking, and effective communication with both technical and non-technical teams **Bonus points:** * Production experience with Computer Vision solutions * Familiarity with tools such as MLflow, Airflow, Kubeflow, or similar * Experience with multi-agent systems and orchestration frameworks * Involvement in creating reusable IP, technical accelerators, or pre-sales functions **Who are we?** We are Glintt Global, a leading consulting and technology services company in the Iberian Peninsula, with over 30 years of experience. We aim to impact people's quality of life through innovation, technology, knowledge, and ambition—this is our commitment! Learn more about our global culture \| Glintt Global!