Machine Learning Engineer - Speech & Natural Language

Primordial Labs is hiring a Machine Learning Engineer to build and own speech recognition and natural language understanding models for its Anura autonomous-systems interface. The role focuses on creating domain-specific data and models, optimizing them for reliable low-latency deployment on constrained hardware, and improving evaluation and MLOps.

Responsibilities:

• Evaluate and Decide: Assess candidate architectures and modeling approaches against the criteria that actually matter operationally: accuracy under degraded conditions, latency, and footprint. Make the call and defend it with data, not vibes
• Build the Data Engine: Develop synthetic data generation tooling and augmentation pipelines, and curate the data we collect from the field. Our accuracy advantage comes from data we build ourselves, and you'll own that machinery
• Train for the Domain: Train and fine-tune models that understand how operators actually talk, in noisy environments and with degraded audio, using language no general-purpose model has seen enough of
• Optimize Ruthlessly: Every millisecond of latency and every megabyte of memory is a design decision with operational consequences. You'll find the wins and prove them with benchmarks
• Mature the Deployment: Turn research-grade code into something we can ship: model weights served directly through an efficient production runtime, with the experimental scaffolding stripped out
• Close the Loop: Own how we measure success. Build evaluation that reflects whether an operator's command actually worked, not just how a model scores on a test set, and turn field failures into test cases, training data, and fixes that stick
• Sharpen Our MLOps: Improve how we train, track, evaluate, and release models. At minimum, be relentlessly vocal about what's broken