Salary
💰 $170,000 - $280,000 per year
Tech Stack
FFmpegGoPythonPyTorchTensorflow
About the role
- Drive ML systems and platform engineering efforts across e2e research & engineering workflows
- Scale training, inference, and evaluation systems and improve reliability of model deployments, operations, and versioning
- Advance enterprise video solutions by incorporating research into fault tolerant, low latency e2e systems
- Scale multimodal AI/ML systems for video understanding
- Deliver applied research solutions such as VLM finetuning, auto-labeling of video-text datasets, and model-based filtering to optimize model performance
- Build high-impact libraries and services
Requirements
- 2+ years of relevant industry experience
- Strong Python coding skills
- Experience with modern ML frameworks (i.e. PyTorch, Tensorflow)
- Excellent problem-solving skills and attention to detail
- Experience with at least one statically typed language (we use Golang) [strong candidates]
- Experience building 0-to-1 mission critical AI/ML applications from scratch [strong candidates]
- Experience optimizing model inference (TensorRT, ONNX, Triton Inference Server) [strong candidates]
- Experience working with FFmpeg or other high performance image/video processing libraries [strong candidates]