Memory-Driven AI Product Engineer

Ando; San Francisco (CA); On-site; USD 150,000 - 210,000; Full time

Benefits offered by this job

Free Equinox membership

Equity grant (4 years vesting)

Health, dental, vision insurance

Job summary

Ando is a bold research-backed messaging platform in San Francisco seeking to push the boundaries of agent-enabled collaboration. You’ll join a small, fast-moving team working close to data and product to build robust evaluation on real workspace data.

The role emphasizes experimentation, collaboration with researchers and product teams, and publishing meaningful progress. Candidates should bring strong applied research, evaluation, and communication skills and enjoy working with imperfect data.

Qualifications

• Strong applied research background with depth in model evaluation, benchmarking, and/or failure analysis.
• Evidence over credentials with work samples or code demonstrating eval frameworks, benchmark suites, or tooling.
• Strong technical communication to explain complex ideas with researchers and product teams.
• Comfort with messy, incomplete workspace data and edge cases.
• Bonus: familiarity with simulation, human-in-the-loop evaluation, memory/compression work, or agent observability tooling.

Responsibilities

• Build evaluation from real data, designing label schemas and rigorous labelling pipelines.
• Run experiments that ship, bridging offline data and production systems.
• Decide what to build in-house versus with partners, evaluating frontier vendors and teams.
• Publish when meaningful progress is achieved, contributing final results to stakeholders.

Skills

Applied research

Model evaluation

Benchmarking

Experiment design

Technical communication

Langsmith

Tools

Langsmith

Job description

Ando is a bold research-backed messaging platform in San Francisco seeking to push the boundaries of agent-enabled collaboration. You’ll join a small, fast-moving team working close to data and product to build robust evaluation on real workspace data.

The role emphasizes experimentation, collaboration with researchers and product teams, and publishing meaningful progress. Candidates should bring strong applied research, evaluation, and communication skills and enjoy working with imperfect data.