Product Lead, Learning Technology

present of AI; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Speak, an AI language tutor app, is seeking a product leader to direct the technical roadmap of the tutor's AI components—voice, memory, content, and evaluation. The role emphasizes hands-on decision-making and close collaboration with engineers and PMs to drive measurable improvements in learners’ conversations.

The ideal candidate has shipped AI/ML systems to production, can balance model behavior with latency, reliability, and cost, and has experience hiring or coaching product managers.

Qualifications

• Decision making for AI product direction
• Experience shipping AI/ML to production
• People leadership/mentoring PMs
• Knowledge of voice, memory, and content systems (bonus)

Responsibilities

• Set product direction for the AI language tutor's technical components (voice, memory, content, evaluation) with measurable impact.
• Evaluate model behavior, latency, reliability, and cost with engineering partners.
• Directly ship prototypes to production and learn from failure modes and latency/cost tradeoffs.

Job description

This role sets product direction for the technical pieces behind an AI language tutor: voice, learner memory, generated content, and the evaluations that judge quality. A strong candidate has shipped AI or ML systems to production with measurable results, can weigh model behavior, latency, reliability, and cost with engineers, and has hired and coached product managers. It is hands on, so the person also stays close to the hardest technical product calls rather than only managing.

How it fits the AI era

The work sits at the center of how AI changes language learning, since the tutor depends on speech recognition, speech generation, memory, and content generation working together. Much of the judgment stays human: deciding which model to adopt, build, or stop, and tying benchmarks to what learners actually experience in lessons. The role is less about writing models and more about choosing where AI investment pays off for learners.

How it builds AI experience

The job offers direct exposure to voice models, agent systems, learner memory, and evaluation design for a conversation based tutor used across many languages and markets. Someone could build this by running evaluations of model output, shipping a prototype into real use, and learning to read failure modes, latency, and cost tradeoffs. Experience with LLMs, agents, or speech technology helps but the posting treats it as a plus, not a requirement.

Worth showing

• Shipped AI to production
• Model evaluation and benchmarks
• Build buy or stop calls
• Managed and coached PMs
• Voice and LLM systems

This is our own read, written from the employer's posting and the company's Spotlight. The employer's posting is the source of truth for the role.

About Speak

An AI language tutor app that gets learners talking, with spoken conversation practice and real-time feedback.