We Love AI JobsAI Engineer
MarlabsThis role builds and deploys AI services for tasks such as entity resolution, event clustering, classification, and document intelligence. You will connect machine-learning models to production systems and work with architects, data engineers, and business stakeholders.
Skills & Expertise
Key Responsibilities
Develop models for entity resolution, event clustering, classification, and relevance scoring.
Build retrieval, evidence-linking, and confidence-based validation workflows for explainable AI outputs.
Deploy and monitor production AI services while improving model precision, recall, and performance.
Full Description
Marlabs, a global AI and Digital Solutions Consulting firm, delivers intelligent solutions across AI, data, analytics, and product engineering. Since 2000, we have partnered with some of the largest healthcare, life sciences, financial services, and government organizations worldwide. As we continue to expand our global footprint, we have an exciting opportunity for a highly skilled AI Engineer to join our innovative and dynamic team.
AI Engineer | About You
As an AI Engineer, you will design and implement advanced AI solutions that support intelligent decision-making, entity resolution, event correlation, relevance ranking, and document intelligence capabilities. You will bridge machine learning models and production systems to deliver scalable AI-powered business solutions.
AI Engineer | Day-to-Day
• Develop AI models supporting entity resolution, event clustering, classification, and relevance scoring.
• Build retrieval and evidence-linking workflows for explainable AI outputs.
• Design confidence-based review and validation frameworks.
• Optimize AI model precision, recall, and performance metrics.
• Deploy and monitor AI services in production environments.
• Collaborate with architects, data engineers, and business stakeholders.
AI Engineer | Skills & Experience
• 5+ years of AI/ML engineering experience.
• Strong Python, NLP, machine learning, and LLM expertise.
• Experience with RAG, vector databases, embeddings, and semantic search.
• Knowledge of precision/recall optimization and model evaluation techniques.
• Experience deploying AI applications in cloud environments.