Senior Applied ML Researcher

Technical Excellence

• [REQUIRED] 5+ years of experience in deep learning research with focus on large-scale model training
• [REQUIRED] Demonstrated experience training models at scale (100M+ parameters) from scratch
• [REQUIRED] Deep understanding of transformer architectures, attention mechanisms, and modern training techniques (mixed precision, distributed training, gradient accumulation)
• Production experience with ML systems at scale (PyTorch, distributed training, model serving)
• Experience with language model pre-training, including tokenization strategies, training objectives (CLM, MLM), and scaling laws
• Understanding of fine-tuning techniques including instruction tuning, RLHF, and preference optimization (DPO, PPO)
• Knowledge of efficient training techniques: LoRA, QLoRA, flash attention, gradient checkpointing
• Experience with model evaluation, benchmarking, and safety considerations

Systems Experience

• Background in vision-language models or multimodal architectures strongly preferred
• Experience building and optimizing data pipelines for large-scale training
• Systems-level thinking about training efficiency, hardware utilization, and cost optimization
• Familiarity with MLOps for model versioning, experiment tracking, and reproducibility

Preferred Qualifications

• Advanced degree (M.S./Ph.D.) in Computer Science, Electrical Engineering, or related field with focus on deep learning
• First-author publications at top ML venues (NeurIPS, ICML, ICLR, ACL, CVPR) on language models, multimodal learning, or efficient training
• Experience training or contributing to open-source foundation models
• Background in domain-specific model development (code, science, medical, etc.)
• Experience with video understanding models or temporal reasoning in transformers
• Contributions to major ML frameworks or training libraries
• Track record of transitioning research prototypes to production systems

Location & Compensation

• San Francisco Bay Area (on-site)
• Competitive salary and significant equity package
• Full benefits including health, dental, vision, and 401k +6% match
• Access to dedicated GPU compute resources for research and experimentation

Compensation

The base pay range for this role is $180,000 – $350,000 per year.

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Req ID: R2D5