Member of Technical Staff, Research Engineering

About the Company

Listen teaches AI what people actually think and want. We're Sequoia-backed, have raised $100M, and our customers include Anthropic, Google, and Cursor. As AI improves at building things, the bottleneck shifts to knowing what to build. We bridge AI systems and human desires by running AI-moderated video interviews at massive scale, surfacing insights in hours instead of weeks.

Our platform maintains a database of millions of people, matching profiles using voice, face, and device IDs to track opinion changes, prevent fraud, and find niche audiences. We're building a Human API where AI agents can query human preferences in real time, enabling closed-loop product development at AI speed.

Company Highlights

• Series B with $100M raised from Sequoia, Conviction, Ribbit, AI Grant, and Pear VC
• Selective team of <20 engineers including VC-backed founders, IOI medalists, and engineers from Jane Street and Tesla Autopilot
• Customers include Anthropic, Cursor, Perplexity, Google, Microsoft, Robinhood, Nestlé, P&G, and Sweetgreen
• 20x year-over-year revenue growth post-PMF
• Clear path to $1M+ contracts at over 50% of the Fortune 2000

Technical Challenges

• Database of Humanity: Maintain a database of millions of people, matching profiles based on voice, face, and device IDs to track opinion changes, prevent fraud, and find niche audiences.
• Emotional Intelligence: Bridge the gap between what people say and think by reading tone, hesitation, and facial micro-expressions to go beyond transcripts.
• Preference Model: Tackle research problems like determining what we already know, when to refresh data, which questions yield the highest signal, and how to quantify uncertainty in predictions.
• Human API: Embed our human preference model into Slack, Linear, IDEs, and coding agents, enabling agents to query human desires and iterate in real time.
• Agent Evals: Build AI-first tools like Study Composer (for scoping studies) and Research Agent (for analyzing responses and writing reports), with a focus on evaluating qualitative outputs to enable continuous improvement.

What We Look For

• End-to-end problem solvers: Engineers own vertical slices of the product, making decisions across the LLM pipeline, infrastructure, backend, and UX.
• Future or past founders: You scope your own work, think about customers, and own your decisions.
• Attention to detail: You prioritize getting things right, aiming for 100% solutions over 80%, and go to root cause when things break.
• LLM enthusiasts: You’re excited about pushing LLMs to their limits, working directly with frontier model labs on new releases, and probing where they break.
• Strong written communication: You articulate complex ideas in writing, as we work independently with minimal meetings.
• Highly technical: Most of the team started coding as teenagers and geek out on details from language design to compilers.

Life at Listen Labs

• Competitive Compensation: Offers include a base salary range of $180,000 – $300,000, with meaningful equity. Actual compensation depends on skill set, experience, and work location.
• Benefits: Comprehensive healthcare and dental coverage, flexible time off, and a work environment that values balance and trust.
• Growth Opportunities: Take on new responsibilities, shape processes from scratch, and grow alongside the company.