2026 - Senior AI/ML Engineer - Multimodal Content Intelligence - Contractor

Location: Dublin, Ireland

About The Role

We are looking for a Senior Machine Learning Engineer to drive the development of our next generation content intelligence systems. In this role, you will be a key technical contributor in developing complex multimodal understanding solutions across video, audio, image, and text. Leveraging cutting edge Multimodal Large Language Models (MLLMs), you will build and optimize a self evolving content analysis ecosystem. Your work will be instrumental in enhancing our core recommendation engine, directly impacting product performance and user engagement through advanced content signals.

Key Responsibilities

• Develop & optimize multimodal frameworks focused on semantic understanding, narrative reasoning, and high level content interpretation.
• Own end to end development of high performance systems that drive algorithmic innovation and resolve high impact technical bottlenecks.
• Work closely with cross functional teams to integrate content signals into production recommendation and discovery pipelines.
• Ensure models are accurate and optimized for low latency inference and high concurrency production environments.

Requirements

• Education: Master's or PhD in Computer Science, AI, Machine Learning, or a related quantitative field.
• Experience: 5-8+ years of professional experience in AI/ML research or advanced engineering (industry experience preferred).
• Technical Depth: Strong hands on experience in at least two of the following:
• Multimodal learning - integration of video, text, image, and audio signals.
• Computer vision - video understanding, temporal modeling, or representation learning.
• NLP - semantic modeling, content quality assessment, or news stream analysis.
• Frameworks: Expert proficiency in PyTorch, TensorFlow, or JAX.
• MLLM/VLM Expertise: Practical experience working with or fine tuning Multimodal Large Language Models.
• Production Skills: Proven track record of deploying large scale AI models in production environments.

Preferred Qualifications

• Track record of contributions to high impact projects or publications in top tier conferences (e.g., CVPR, ICCV, NeurIPS).
• System Design: Experience building automated content tagging or recommendation signals from the ground up.
• Domain Knowledge: Familiarity with digital signal processing for audio or aesthetic evaluation for images/video.