Multimodal ML Engineer (AI)

TL;DR

Multimodal ML Engineer (PyTorch/Multimodal AI): Training and shipping vision, audio, video, and speech models for an AI safety platform with an accent on large-scale multimodal architecture and production optimization. Focus on building alignment pipelines, optimizing MoE architectures for efficient inference, and designing evaluation metrics for complex multimodal reasoning.

Location: Must be based in or able to relocate to Paris or London (Hybrid)

Salary: $120K – $250K + Equity

Company

hirify.global is an AI Safety company building the safety, reliability, and optimization layer for AI systems.

What you will do

• Train and fine-tune large-scale multimodal models (vision, audio, speech) from scratch and from pretrained checkpoints.
• Extend models across modalities, including image understanding, video temporal modeling, and streaming audio.
• Design and execute experiments focusing on architecture changes, data mixes, and training recipes.
• Build and maintain multimodal data pipelines and generate synthetic data for training.
• Optimize MoE architectures for inference and deploy models end-to-end from research to production.
• Define critical evaluation metrics and benchmarks for visual QA, spatial reasoning, and audio understanding.

Requirements

• 3+ years of experience training large-scale deep learning models in multimodal domains.
• Strong PyTorch skills with hands-on distributed training experience (DeepSpeed, FSDP).
• Deep understanding of multimodal architectures such as LLaVA, Qwen-VL, Whisper, or similar.
• Experience with RLHF/alignment techniques (GRPO, DPO, reward modeling) for multimodal data.
• Proven track record of shipping optimized models to production with a focus on latency targets.
• Must be based in or able to relocate to Paris or London.

Nice to have

• Understanding of audio signal processing fundamentals, including spectrograms and mel features.

Culture & Benefits

• Paid time off in accordance with local regulations.
• Relocation package available for candidates moving to Paris.
• Comprehensive medical insurance for the France-based team.
• Full provision of hardware, tools, and paid subscriptions for AI agents and IDEs.
• Bi-annual team off-sites (e.g., Alps, Saint-Tropez).

Hiring process

• Introductory HR call (25 min).
• Take-home technical test task.
• Technical interview with the Head of Applied Research (60 min).
• Final conversation with the CEO (45 min).