Software Engineer - Applied AI
LocationLondon
Posted2 hours ago
At Hudson River Trading (HRT) the Applied AI team’s mission is to increase the speed and quality of work across the firm’s most consequential workflows. We build AI systems that help researchers and developers iterate faster, automate increasingly complex work, and enable autonomous exploration at a scale that would not otherwise be possible.
We apply frontier models and agentic systems to how quantitative research, software development, and other critical work at HRT gets done. We combine cutting-edge commercial and open-source models and tools with infrastructure, research, and systems of our own.
Our work spans the full stack required to make this successful: AI infrastructure, research engineering, post-training and reinforcement learning, agent evaluation, security and alignment, and deployment into real workflows.
Responsibilities
Building scalable infrastructure for training, evaluating, and operating language models and AI agents
Developing research environments, evaluation systems, and experimentation platforms that allow us to measure and improve agent performance
Improving model and agent capabilities through post-training, reinforcement learning, prompting, tool design, and workflow optimization
Designing sandboxing, policy enforcement, monitoring, and other safeguards for increasingly capable autonomous systems
Partnering with teams across HRT to identify work AI can newly perform, develop effective solutions, and turn successful experiments into durable systems
Evaluating new models, techniques, and products, and making informed decisions about when to build, buy, or adapt them
Sharing technical knowledge and establishing effective practices for building and working with AI across HRT
Profile
You are an excellent engineer who can turn ambiguous problems into working systems
You learn unfamiliar technical and business domains quickly and enjoy moving between them
You care about advancing what AI systems can reliably accomplish
You use rigorous measurement and experiment design to guide decisions
You are comfortable operating across research and production engineering
You communicate clearly and collaborate well with people from different technical backgrounds
You are curious about the capabilities, limitations, and risks of increasingly autonomous systems
Qualifications
Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience required
Strong Python proficiency required
Excellent software design, debugging, and problem-solving skills required
Experience building and operating substantial software systems required
Demonstrated engagement with modern AI systems, tools, or research required
Machine learning research or engineering, including post-training, fine-tuning, reinforcement learning, or alignment
AI-agent architecture, evaluation, or tool-use environments
Distributed systems, model serving, orchestration, or high-throughput research infrastructure
Security sandboxing, policy enforcement, adversarial testing, or governance for AI systems
Forward-deployed engineering: working closely with users to discover, build, and operationalize new capabilities
Linux, systems performance, networking, C++, or TypeScript
The estimated base salary range for this position is 200,000 to 300,000 USD per year (or local equivalent). The base pay offered may vary depending on multiple individualized factors, including location, job-related knowledge, skills, and experience. This role will also be eligible for discretionary performance-based bonuses and a competitive benefits package.
Culture
We apply frontier models and agentic systems to how quantitative research, software development, and other critical work at HRT gets done. We combine cutting-edge commercial and open-source models and tools with infrastructure, research, and systems of our own.
Our work spans the full stack required to make this successful: AI infrastructure, research engineering, post-training and reinforcement learning, agent evaluation, security and alignment, and deployment into real workflows.
Responsibilities
Building scalable infrastructure for training, evaluating, and operating language models and AI agents
Developing research environments, evaluation systems, and experimentation platforms that allow us to measure and improve agent performance
Improving model and agent capabilities through post-training, reinforcement learning, prompting, tool design, and workflow optimization
Designing sandboxing, policy enforcement, monitoring, and other safeguards for increasingly capable autonomous systems
Partnering with teams across HRT to identify work AI can newly perform, develop effective solutions, and turn successful experiments into durable systems
Evaluating new models, techniques, and products, and making informed decisions about when to build, buy, or adapt them
Sharing technical knowledge and establishing effective practices for building and working with AI across HRT
Profile
You are an excellent engineer who can turn ambiguous problems into working systems
You learn unfamiliar technical and business domains quickly and enjoy moving between them
You care about advancing what AI systems can reliably accomplish
You use rigorous measurement and experiment design to guide decisions
You are comfortable operating across research and production engineering
You communicate clearly and collaborate well with people from different technical backgrounds
You are curious about the capabilities, limitations, and risks of increasingly autonomous systems
Qualifications
Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience required
Strong Python proficiency required
Excellent software design, debugging, and problem-solving skills required
Experience building and operating substantial software systems required
Demonstrated engagement with modern AI systems, tools, or research required
Machine learning research or engineering, including post-training, fine-tuning, reinforcement learning, or alignment
AI-agent architecture, evaluation, or tool-use environments
Distributed systems, model serving, orchestration, or high-throughput research infrastructure
Security sandboxing, policy enforcement, adversarial testing, or governance for AI systems
Forward-deployed engineering: working closely with users to discover, build, and operationalize new capabilities
Linux, systems performance, networking, C++, or TypeScript
The estimated base salary range for this position is 200,000 to 300,000 USD per year (or local equivalent). The base pay offered may vary depending on multiple individualized factors, including location, job-related knowledge, skills, and experience. This role will also be eligible for discretionary performance-based bonuses and a competitive benefits package.
Culture
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