Tech Lead – ML/AI Engineering

Glintt Global

. Lead the technical design and implementation of end-to-end ML/AI solutions, from problem definition through production deployment and monitoring .

Posted 10/2/2026full-timeLisbon • PortugalSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in leading the design and implementation of Machine Learning and AI solutions, with a strong focus on model development, MLOps practices, and effective communication across technical and non-technical teams.

Highest-signal resume keywords

Machine Learning Project DeliveryPython ProgrammingGenerative AI ExperienceMLOps PracticesTechnical Leadership

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningDeep LearningFeature EngineeringModel ValidationAPI DevelopmentDistributed SystemsCloud DeploymentComputer VisionMulti-Agent SystemsModel Lifecycle Management

Soft Skills

Effective CommunicationTechnical Team MentoringArchitectural Thinking

Tools & Technologies

MLflowAirflowKubeflowCI/CDExperiment TrackingObservability

Industry Keywords

Generative AIRAGAgent-Based PipelinesTechnical ProposalsPre-Sales Activities

Tech Stack

Tools & technologies

AirflowCloudPython

About the role

Key responsibilities & impact

Lead the technical design and implementation of end-to-end ML/AI solutions, from problem definition through production deployment and monitoring
Define architectures and pipelines for Machine Learning, Computer Vision, and Generative AI, including RAG, embeddings, and agentic systems
Contribute hands-on 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
Work with Data Engineers, MLOps, Product, and business stakeholders to ensure technical and functional alignment
Support pre-sales activities and solution definition, contributing to technical proposals and estimates
Promote component reuse, the creation of accelerators, and technical team mentoring

Requirements

What you’ll need

Strong experience delivering ML/AI projects in production environments
Strong command of Python and the Machine Learning and Deep Learning ecosystem
Hands-on 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 skills, architectural thinking, and effective communication with technical and non-technical teams
Experience delivering Computer Vision solutions in production (preferred)
Exposure to MLflow, Airflow, Kubeflow, or similar tools (preferred)
Experience with multi-agent systems and orchestration frameworks (preferred)
Involvement in creating reusable IP, technical accelerators, or supporting pre-sales activities (preferred)
Valid visa or work authorization for Portugal