Stellenbeschreibung:

This position is posted by Jobgether on behalf of Tether.io. We are currently looking for a Senior AI Engineer - Data & Infrastructure for Multimodal Models in the United Kingdom.

We are seeking a Senior AI Engineer to design and implement scalable, high-throughput data pipelines for cutting-edge multimodal AI research. In this role, you will work closely with model researchers to develop infrastructure capable of handling massive video, audio, text, and image datasets across thousands of GPUs. You will optimize distributed data workflows, automate dataset acquisition, and build systems for evaluation and annotation, contributing to next-generation video and multimodal AI models. This role is ideal for engineers who thrive in fast-paced, high-impact environments and are passionate about pushing the boundaries of AI infrastructure. Collaboration, innovation, and technical excellence are central to success in this position.

Accountabilities:

• Build and scale data infrastructure optimized for large-scale video and multimodal content processing across GPU clusters.
• Design preprocessing algorithms for video, audio, text, and image modalities to enable efficient extraction, synchronization, and normalization.
• Develop automated pipelines for large-scale video dataset acquisition, managing diverse formats, annotations, and embedded audio.
• Architect systems for scalable evaluation, including prompt-based scoring, perceptual metrics, caption generation, and retrieval diagnostics.
• Collaborate with research teams to co-design model architectures and training schedules across pretraining and fine-tuning stages.
• Optimize distributed data loading and pipeline throughput for training at scale, ensuring robustness across model variants.
• Manage infrastructure for experiment tracking, model versioning, and deployment workflows integrated with production and research platforms.
• Support backend engineering for seamless integration of data and model workflows from prototyping to inference.

Requirements

Requirements:

• Proficient in Python with strong programming skills in backend, infrastructure, and data tooling.
• Minimum 2+ years experience building and maintaining petabyte-scale data pipelines and distributed systems across thousands of GPUs.
• Hands-on expertise in orchestration frameworks such as Kubernetes and SLURM for high-throughput workloads.
• Proven ability to architect and maintain large-scale distributed data processing and delivery systems.
• Experience collaborating with AI researchers and understanding model training requirements.
• Strong problem-solving, analytical, and debugging skills in complex infrastructure environments.
• Familiarity with multimodal datasets (video, image, audio, text) and processing pipelines is highly advantageous.
• Experience in building video foundation infrastructure in collaboration with LLM or video AI teams is a strong plus.

Benefits

• Competitive salary and performance-based incentives.
• Flexible working environment with remote options.
• Opportunities to work on cutting-edge AI research with global impact.
• Access to state-of-the-art infrastructure and GPU clusters.
• Professional growth and career development in AI and infrastructure engineering.
• Collaborative, high-performing, and innovation-driven team culture.


Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching.

When you apply, your profile goes through our AI-powered screening process designed to identify top talent efficiently and fairly:
🔍 Our AI evaluates your CV and LinkedIn profile thoroughly, analyzing your skills, experience, and achievements.
📊 It compares your profile to the job’s core requirements and past success factors to determine your match score.
🎯 Based on this analysis, we automatically shortlist the 3 candidates with the highest match to the role.
🧠 When necessary, our human team may perform an additional manual review to ensure no strong profile is missed.

The process is transparent, skills-based, and free of bias — focusing solely on your fit for the role. Once the shortlist is completed, we share it directly with the company that owns the job opening. The final decision and next steps (such as interviews or additional assessments) are then made by their internal hiring team.

Thank you for your interest!

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NOTE / HINWEIS:

EN: Please refer to Fuchsjobs for the source of your application

DE: Bitte erwähne Fuchsjobs, als Quelle Deiner Bewerbung