Senior Multimodal AI Systems Engineer – San Jose

Hark; San Jose (CA); On-site; USD 180,000 - 450,000; Full time

Job summary

Hark is an AI company building advanced, proactive, multimodal intelligence. The Omni team develops multimodal foundation models and long-context data recipes, exploring learning-rate schedules, data mixtures, and distillation to improve model capabilities.

The role focuses on mid-training recipes, synthetic data pipelines, evaluation, and distillation to transfer knowledge into smaller models, enabling efficient, recent AI systems across text, code, and multimodal data.

Qualifications

• Experience with continued pretraining or late-stage training including learning-rate decay.
• Experience building synthetic data pipelines, including generation, verification, and filtering, and evaluating their effects on model quality.
• Strong experimental judgment and ability to isolate recipe changes in controlled ablations.
• Experience implementing and debugging distributed training workloads across GPU clusters.
• Experience designing evaluations and identifying confounds such as benchmark contamination and prompt sensitivity.
• Strong engineering skills and ability to build reliable data and experimentation pipelines.
• Evidence of improving model capabilities or training methods through research, datasets, systems, or production work.

Responsibilities

• Develop mid-training recipes using high-quality and synthetic data, including learning-rate decay schedules and data-mixture changes.
• Build synthetic data pipelines with code execution tests, math-answer checks, and filters for reasoning traces.
• Distill capabilities from larger models into smaller models through synthetic data generation and rejection sampling.
• Develop long-context data recipes, including document packing and sequence construction, and evaluate their effect on both long- and short-context performance.
• Evaluate mid-training checkpoints with the post-training team, measure how well results predict subsequent model quality, and select checkpoints for further training.
• Run controlled experiments on learning-rate schedules, mixture weights, and data ordering across text, code, and multimodal training data.

Skills

Continued pretraining

Synthetic data pipelines

Experimental design

Distributed training

Evaluation & ablations

Model evaluation

Engineering discipline

Multimodal expertise

Job description

Hark is an AI company building advanced, proactive, multimodal intelligence. The Omni team develops multimodal foundation models and long-context data recipes, exploring learning-rate schedules, data mixtures, and distillation to improve model capabilities.

The role focuses on mid-training recipes, synthetic data pipelines, evaluation, and distillation to transfer knowledge into smaller models, enabling efficient, recent AI systems across text, code, and multimodal data.