Founding Research Engineer

Acceler8 Talent; San Francisco (CA); On-site; USD 150,000 - 240,000; Full time

Job summary

Acceler8 Talent is partnering with a fast-growing defence AI startup to hire a Founding Research Engineer. You will build quantitative prediction and agent-learning systems designed to detect and conduct a novel class of AI-powered cyber operation.

If you are a quantitative researcher, developer or applied ML engineer with strong empirical judgement and hands-on coding ability, this role is for you. Experience with noisy time-series, signal processing or behavioural modelling is highly valued,

Qualifications

• Quantitative researcher, developer or applied ML engineer.
• Strong empirical judgement and hands-on coding ability.
• Experience with noisy time-series, signal processing or behavioural modelling.
• Personally owned models from hypothesis through deployment.
• Comfortable with both statistical methods and deep learning.
• High-agency and effective in ambiguous environments.
• Cybersecurity experience is not required.

Responsibilities

• PB-scale multimodal time-series data refreshing in under a second.
• Building streaming and data-capture infrastructure.
• Creating useful representations from noisy, unstructured signals.
• Modelling actor behaviour using statistical models, deep learning and transformers.
• Training agents against sparse, long-horizon rewards.

Skills

Quantitative researcher

Applied ML engineer

Strong coding ability

Time-series analytics

Statistical methods

Deep learning

Job description

Founding Research Engineer, AI & Defence | Quantitative Research | Applied ML

I'm partnering with a fast-growing defence AI startup to hire a Founding Research Engineer

You'll be building quantitative prediction and agent-learning systems designed to detect and conduct a novel class of AI-powered cyber operation

What you'll be working on:

• PB-scale multimodal time-series data refreshing in under a second
• Building streaming and data-capture infrastructure
• Creating useful representations from noisy, unstructured signals
• Modelling actor behaviour using statistical models, deep learning and transformers
• Training agents against sparse, long-horizon rewards

Why join?

• Founding-level ownership across research and production
• Revenue-generating company solving national-scale problems
• Backed by Tier 1 seed investors with significant runway
• Work alongside experienced quantitative and cybersecurity specialists
• Opportunity to help shape the technical team as the company scales

Ideal candidate:

• Quantitative researcher, developer or applied ML engineer
• Strong empirical judgement and hands-on coding ability
• Experience with noisy time-series, signal processing or behavioural modelling
• Personally owned models from hypothesis through deployment
• Comfortable with both statistical methods and deep learning
• High-agency and effective in ambiguous environments
• Cybersecurity experience is not required