Founding Member of Technical Staff, Research

present of AI; San Francisco (CA); Remote; USD 180,000 - 280,000; Full time

Job summary

Present of AI in San Francisco seeks a Founding Member of Technical Staff, Research to build and test simulations of people and markets using machine learning, statistics and behavioural science. You will design agents that improve research, shape training data, environments and evaluation methods, and drive rigorous experiments that advance our agent-native platform.

You bring a strong research track record, deep quantitative training, and solid programming and systems design abilities to help

Qualifications

• Strong quantitative training in ML, statistics or related fields.
• Experience building and testing simulations of people and markets.
• Proven programming and system design abilities.
• Track record of serious research.

Responsibilities

• Build and test simulations of people and markets using ML, statistics, and behavioural science.
• Create agents that improve research and shape training data, environments and evaluations.
• Design experiments and evaluation methodologies for autonomous research agents.

Skills

Machine learning

Statistics

Behavioural science

Programming

System design

Research track record

Job description

Founding Member of Technical Staff, Research

AI & Data San Francisco, CA, US / London, England, GB / Warsaw, Masovian Voivodeship, PL / Remote (US) Full-time

The role asks for someone who can build and test simulations of people and markets, drawing on machine learning, statistics and behavioural science. It also involves creating agents that improve their own research and shaping the training data, environments and evaluations behind them. A strong candidate brings deep quantitative training, a record of serious research, and solid programming and system design ability.

How it fits the AI era

The work sits at the centre of how AI is reshaping market research, with agents handling the asking, analysing and simulating. What stays human is judgement about which methods are sound, how to measure whether a simulation is any good, and how to design experiments that mean something. The role is less about running studies by hand and more about building the systems that run them.

How it builds AI experience

A person here would gain hands on practice fine tuning models, designing reinforcement learning environments, and building evaluations for autonomous research agents. That experience maps directly to the company goal of agents that interview experts and turn answers into market simulations. Building proof of work in agent evaluation or simulation design would show readiness for this kind of role.

Worth showing

• Machine learning methods
• Experiment and eval design
• Statistical and behavioural analysis
• Programming and system design
• Research track record

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 LATO

LATO is an agent-native research platform that, per the company, sources and interviews hundreds of verified domain experts and customers, then combines those interviews with thousands of documents into a single commercial study.