Research Engineer

Acceler8 Talent; San Francisco (CA); On-site; USD 180,000 - 300,000; Full time

Benefits offered by this job

Significant equity

Job summary

Acceler8 Talent is assembling a small, high-agency team to tackle defense AI problems at scale. The role blends quantitative research with applied ML, focusing on petabyte-scale, multimodal time-series data and a fast-moving learning stack.

You will influence core technology choices as an early engineering hire, with base salaries up to $300k plus meaningful equity. Prior cyber experience is not required, and US work authorization is needed.

Qualifications

• Highly quantitative with hands-on ML experience.
• Experience solving highly ambiguous research problems in data-intensive settings.
• Background in quantitative research or data-driven domains is preferred.

Responsibilities

• Build the prediction and learning stack for petabyte-scale, multimodal time-series data.
• Stream and refresh data in under one second at scale and convert signals into useful representations.
• Model future actor behavior within complex environments using both classical statistics and deep learning.
• Develop agents that learn new strategies from sparse, long-horizon rewards and contribute to technical direction as an early engineer.

Skills

Quantitative

Time-series

Machine learning

Deep learning

Transformers

Tools

Python

PyTorch

NumPy

Job description

I’m working with a highly ambitious defense AI startup building technology to detect and conduct a novel class of AI-powered cyber operation. This is not conventional cybersecurity, vulnerability research or zero-day hunting.

The technical challenge sits much closer to elite quantitative research, market microstructure and applied machine learning.

You’ll work with petabyte-scale, multimodal time-series data refreshing in under one second, helping build the full prediction and learning stack:

• Stream and capture continuously refreshing data at scale
• Convert noisy, often ungrounded signals into useful representations
• Model the future behaviour of actors within complex environments
• Combine classical statistical methods with deep learning and transformers
• Build agents that learn new strategies from sparse, long-horizon reward signals
• Shape the technical direction of the company as an early engineering hire

The strongest candidates will be highly quantitative, empirically minded and comfortable working on ambiguous research problems. You may currently be a Quantitative Researcher or Quantitative Developer within a top systematic trading environment.

Relevant backgrounds could also include:

• Systematic trading and market microstructure
• Machine learning and sequential modelling
• Computational social science
• Intelligence or national-security technology

Prior cybersecurity experience is not required.

The company is already revenue-generating, has more than 18 months of runway and is backed by leading seed investors. The founding team has built and exited multiple companies, collectively returning more than $1B to investors.

Its advisory network includes senior military leaders and former White House advisors.

This is an opportunity to join a small, high-agency team working on problems with direct defense and intelligence relevance, where the earliest hires will influence both the core technology and how it is deployed.

Base salaries up to $300k + Significant equity for founding Engineers

No export controls, but you will need to either be a Green Card holder or US citizen to apply.