ML Engineer

What we're looking for

• Python and ML engineering skills across the full model development

lifecycle: data pipelines, training, evaluation, and deployment

• Experience with encoder architectures, autoregressive models, or self-

supervised pre-training approaches (e.g. Masked Autoencoders)

• Familiarity with CoreML, MLX, or comparable inference frameworks

• Comfortable working from data pipeline to model serving to a

lightweight frontend

• C or C++ experience is a plus for inference porting work

• Experience with curriculum learning or training-data scheduling

strategies is a plus

Example of work tasks

• Improve encoder models: increase model capacity and input

resolution.

• Build multi-classification support for a range of map-feature attributes

— end-to-end: data pipeline, model training, and evaluation

• Port a large-scale inference pipeline to C, build a CLI and frontend for

job management, and create a plugin interface for viewing results

• Port CoreML inference to MLX, enabling cross-OS model execution

• Train a confidence and ranking model on top of existing autoregressive

model outputs

• Implement curriculum training: rank tasks by difficulty and automate

progressive scheduling of training data