AI Engineer
Own our AI models end-to-end: dataset strategy, training/fine-tuning, evaluation, optimization, and deployment to real hardware in the field. You'll turn messy real-world streams into robust, low-latency inference pipelines.
What you'll do
- Design, train, and fine-tune text/audio/vision models (e.g., DistilRoBERTa, wav2vec2, YOLO) for threat and aggression detection.
- Build reproducible training pipelines (HF/ PyTorch/ SpeechBrain), incl. PEFT/LoRA, adapters, and transfer learning.
- Optimize for real-time: quantization, pruning, ONNX/TensorRT, mixed precision, batching, caching.
- Ship models to edge & cloud with CI/CD, versioning, and rollback; instrument latency and accuracy SLAs.
- Create data pipelines: collection, labeling, augmentation/synthesis, dataset versioning (DVC).
- Collaborate with backend/infra on streaming (RTMP/TCP), Pub/Sub, autoscaling, and observability.
Must haves
- Python wizardry and strong PyTorch.
- Hands-on experience with Audio/Video AI - HuggingFace Transformers, SpeechBrain or torchaudio, one detection/pose stack (YOLO, MediaPipe).
- Production MLOps: experiment tracking, model registries, CI/CD, model monitoring.
- Comfortable with GCP, containers, and GPUs.
- Located in London or ready to relocate.
Nice to haves
- Real-time inference experience
- Streaming systems, low-latency audio (VAD/Whisper/wav2vec2), and CV pipelines.
- Security/privacy by design (PII handling, encryption, GDPR).
- Experience tuning multi-objective metrics (precision/recall trade-offs for safety-critical apps).
The deal:
- Full-time
- London-based (or ready to relocate)
- One-month probation to confirm you have what it takes
- Career-defining opportunity
- Competitive London salary + share options