Services
Senior deep-learning engineering, billed hourly.
LayerGenius works on applied deep-learning problems in the Keras ecosystem — vision, time-series, and tabular — for teams that need models to hold up in production, not just in a notebook. Every engagement is hourly time & materials with senior US engineers, run as a project or as staff augmentation alongside your team. Scope, staffing, and timeline are agreed in an initial conversation.
Four service lines cover the life of a model:
Model & pipeline review
An audit of what you already have: model architecture, tf.data input pipeline, training stability, evaluation methodology, and the serving path. You get prioritized findings with measured improvement targets.
Applied model development
Building models that solve the stated business problem — problem framing, dataset curation, transfer learning and fine-tuning, and training that is documented and reproducible.
Keras 3 & backend modernization
Moving legacy TF1.x and tf.keras code to Keras 3, opening up the JAX and PyTorch backends, and capturing the performance headroom: mixed precision, distribution strategies.
Deployment & MLOps
Serving with TF Serving, ONNX, or LiteRT on edge devices; model versioning, drift monitoring, and retraining pipelines.
Not sure which line fits? Most engagements start with a review — it is the fastest way for both sides to see the real state of a system.