Cutting Edge

We recruit machine learning researchers responsible for alpha generation, predictive modelling, and systematic signal development. These hires work on feature engineering, model training, and research pipelines using large-scale datasets. We assess candidates on their ability to deliver implementable research that performs under real market constraints rather than theoretical assumptions.

We place quantitative researchers who combine machine learning with traditional statistical modelling. These professionals often focus on market microstructure, short-horizon prediction, and strategy optimisation. In prop trading AI hiring, these hires are often critical to improving signal robustness and building repeatable research processes.

We recruit applied AI engineers who operationalise models and integrate them into live trading environments. These hires build pipelines, manage deployment workflows, and ensure model outputs are delivered with reliability and speed. They often sit at the intersection of research and trading, ensuring that AI systems can function effectively under real-time market conditions.

Many prop firms require engineering capability specifically focused on execution speed and infrastructure. We support prop trading AI hiring for low latency engineers who build high-performance systems, optimise data handling, and integrate AI signals into execution engines. These hires are central for market making firms and systematic prop shops operating in highly competitive environments.

AI research depends on clean and scalable data. We recruit data engineers who build ingestion pipelines, maintain tick data environments, and ensure that researchers have reliable access to structured datasets. These hires are critical for firms scaling research output and expanding into new markets.

As AI models are deployed into live trading, monitoring and governance become essential. We recruit MLOps professionals responsible for deployment automation, performance tracking, drift detection, and model version control. These hires ensure that models remain stable and can be adjusted quickly when market conditions change.

Prop firms increasingly apply AI to real-time risk monitoring, portfolio exposure management, and scenario analytics. We recruit candidates who build risk engines and analytics tools that support traders and leadership in maintaining disciplined exposure through volatile market conditions.

We support senior hiring including heads of machine learning, heads of AI research, and technical leaders responsible for building AI divisions. These individuals shape research culture, define process, and align AI development with commercial trading goals. Prop trading AI hiring at this level requires candidates with both technical credibility and the ability to operate in high-performance environments.

Prop trading AI hiring requires access to elite talent and a deep understanding of how machine learning translates into execution advantage and systematic edge. HW Anderson is well positioned to support proprietary trading firms of all sizes, from high frequency market makers through to multi-asset systematic platforms, as they build AI capability across research, engineering, and trading infrastructure.