Founding Machine Learning Engineer

About the role

The Founding Machine Learning Engineer will build and enhance post-processing pipelines that clean, validate, and package large volumes of video and audio data for multimodal model training. This role involves handling wide variation in speech, visual quality, and format, making robustness a significant engineering challenge.

Responsibilities

• Build and enhance post-processing pipelines that clean, validate, and package large volumes of video and audio data for multimodal model training.
• Deploy and fine-tune open-source models for speech recognition, speaker diarization, video segmentation, and related tasks.
• Design infrastructure for large-scale distributed processing, parallelizing thousands of compute jobs across cloud platforms and optimizing for throughput and cost.

Requirements

We are looking for candidates with strong experience in ML infrastructure, speech/audio processing, or large-scale data pipelines. Proficiency in PyTorch is required, along with familiarity with distributed job orchestration.

Qualifications

• Strong experience in ML infrastructure, speech/audio processing, or large-scale data pipelines.
• Proficiency in PyTorch.
• Familiarity with distributed job orchestration.
• A bias toward shipping. You default to building, not theorizing.
• Ability to work effectively in an early-stage environment where scope is broad and priorities shift fast.

Skills

• Experience at a data company or frontier AI lab.
• Track record building pipelines that process tens of thousands of hours of audio or video.
• Experience with infrastructure cost optimization or model fine-tuning for production use.

Benefits

Commensurate with experience.

Pay

TBD

Schedule

TBD

Benefits

Commensurate with experience.