Senior Machine Learning Engineer

Responsibilities

• Architect, train, and optimize multitask deep learning models across multimodal sensor streams.
• Build automated data-mining pipelines, active-learning loops, hard-example curation, and auto-labeling systems.
• Develop high-resolution vision architectures and spatiotemporal transformer backbones.
• Use multimodal foundation models for automated data curation, synthetic edge-case generation, and failure triage.
• Profile and optimize models for efficient onboard accelerator inference.

Requirements

• 2–5+ years of experience training and deploying production vision or multimodal deep learning models.
• Experience with multimodal sensor fusion involving camera, LiDAR, and audio.
• Experience with multitask learning, transformer architectures, and PyTorch or JAX.
• Experience building large-scale data-curation pipelines, active-learning loops, and auto-labeling systems.
• Fluency with modern AI developer tools and foundation-model workflows for rapid prototyping.

Benefits

• Hybrid work arrangement.
• Full-time employment.
• Eligibility for a discretionary annual bonus program, equity incentive plan, and company benefits program, subject to eligibility requirements.