Research Engineer, Agentic Systems
Build and advance agentic machine-learning systems for multimodal creative tasks, with a focus on video understanding, reasoning, control, and tool use. The role requires strong production ML or agent-pipeline experience and deep knowledge of modern LLM techniques.
About the job
Responsibilities
- Design and build end-to-end agentic systems for creative tasks.
- Develop novel approaches for training and adapting large language models that power agentic systems.
- Design objectives, datasets, and fine-tuning strategies to improve agent behavior and reliability.
- Explore multimodal reasoning and structured generation for creative control.
- Run systematic experiments to evaluate and improve agent performance in real-world tasks.
- Design evaluation frameworks for agentic workflows in video analysis and editing.
- Analyze failure modes across planning, tool use, and execution, and iterate on improvements.
Requirements
- BS, MS, or PhD in computer science, machine learning, or a related field.
- Strong track record building production machine-learning systems or agentic pipelines.
- Deep understanding of transformers and modern large language model techniques.
- Experience with fine-tuning, alignment, or post-training methods, particularly for structured outputs or tool use.
- Ability to own the full stack from model-level experiments to deployed agent systems.
- Strong experimental rigor and practical judgment about agent performance.
Benefits
- Medical, dental, and vision plans.
- 401(k) with employer match.
- Commuter benefits.
- Catered lunches multiple days per week.
- Dinner stipend and Grubhub subscription.
- Health and wellness perks.
- Team offsites and monthly team events.
- Generous paid time off.
Skills
Machine Learning, Agentic Systems, LLMs, Transformers, Multimodal Reasoning, Fine-Tuning, Model Alignment, Post-Training, Structured Generation, Tool Use, Video Analysis, Evaluation Frameworks
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