Part-Time AI Research Data Annotator

AI Research Data Annotator (Part-Time)

Location: San Francisco, CA (On-site)

Type: Part-time contract, approximately 15–20 hours per week

Compensation: $20–$25/hour

About Engramme

Engramme is an AI research lab building Large Memory Models (LMMs) to give people perfect, infinite memory.

We're founded by Gabriel Kreiman, a former Harvard professor, and Spandan Madan, a former Harvard researcher. We're a small, ambitious team in San Francisco working on one of the most fundamental challenges in AI: memory.

About the Role

We're looking for part-time AI Research Evaluators / Data Annotators to help us train, evaluate, and improve our AI memory system.

Our technology connects information from everyday digital tools—such as email, messages, and documents—and surfaces relevant memories when they're useful.

You'll work directly with our research team on a variety of data labeling and evaluation tasks. These tasks are essential to developing and improving our Large Memory Models.

Examples of tasks include

• AI Memory Evaluation: Use Engramme's AI memory system during everyday digital activities and evaluate whether the memories it retrieves are relevant and useful.
• Conversation Annotation: Review transcripts of recorded conversations and identify specific statements, facts, experiences, and other information that represent memories.
• Memory Classification: Examine AI-generated memories and classify them based on criteria such as whether they contain spam, irrelevant information, or other undesirable content.
• Research Data Annotation: Label and categorize different types of memory-related information to help researchers develop and train new algorithms.
• Research Experiments: Participate in structured experiments, which may include recorded conversations with appropriate consent, and assist with other emerging data collection and labeling tasks.

Because we're developing a new category of AI, the specific tasks will evolve over time. You'll receive instructions and training for each task and work closely with our researchers to refine how memory data is evaluated and annotated.

This is a hands-on data evaluation and annotation role, not a software engineering or AI research scientist position.

What You'll Do

• Complete a variety of data annotation and evaluation tasks during scheduled in-office sessions.
• Review text, conversation transcripts, and AI-generated memories to produce accurate, consistent labels.
• Use Engramme's memory system during everyday digital activities and provide feedback on the relevance and usefulness of retrieved memories.
• Apply task-specific annotation guidelines and exercise judgment when encountering ambiguous information.
• Complete a high volume of careful, consistent annotations while maintaining quality standards.
• Identify unclear instructions, edge cases, and recurring issues, and share observations with our research team.
• Adapt to new annotation tasks as our research priorities and experiments evolve.

What We're Looking For

• Strong attention to detail: You can carefully examine information and make consistent, well-reasoned judgments.
• Reliability and consistency: You're comfortable performing repetitive tasks accurately over extended periods.
• Good judgment: You can interpret nuanced instructions and recognize when an example is ambiguous or requires clarification.
• Adaptability: You're comfortable learning new tasks and working with guidelines that may evolve as our research progresses.
• Digital literacy: You're comfortable using web browsers, email, messaging applications, and other everyday digital tools.
• Clear communication: You can explain your reasoning, flag unclear cases, and provide constructive feedback.
• Availability: You can work approximately 15–20 hours per week in person at our San Francisco office.
• Must be at least 18 years old.

Some evaluation tasks may involve connecting your own digital information to our system, subject to informed consent and appropriate privacy protections.

No prior AI, programming, or research experience is required. College students and recent graduates are welcome to apply.

Why Join Us?

• Contribute directly to cutting-edge AI research and help develop a new category of AI technology.
• Work alongside researchers and engineers developing Large Memory Models.
• Gain firsthand exposure to how AI systems are trained, evaluated, and improved.
• Help shape annotation guidelines and evaluation methods for an emerging area of AI research.
• Enjoy flexible part-time scheduling and a collaborative in-office environment.