Machine Learning Engineer

Requirements:

· 8+ years of experience building production ML inference systems.

· Demonstrated ownership of deep-learning inference optimization in production (quantization, distillation, compilation, kernel/profile-level performance work) for transformer NLP and/or CV models.

· Experience with both TensorFlow (SavedModel, tf.data, XLA, TFLite) and PyTorch (TorchScript, ONNX, FastAPI/TorchServe)

· Hands-on experience optimizing inference pipelines on AWS infrastructure, ideally across different types of media assets.

· Experience with video frameworks/tools (e.g., FFmpeg), and working with large-scale frame-level inference.

· Demonstrated experience monitoring and debugging model latency, memory, and pipeline throughput.

· Experience with hybrid search architectures (BM25 + vector search + cross-encoder reranking).

· Familiarity with OpenAI APIs or other foundation model providers.

· Familiarity with open source HuggingFace LLMs.

· Experience with data pipeline and workflow orchestration tools (e.g., Airflow)