3 months ago

Member of technical staff - Agent

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 1 day agoStatus: Live

Job Summary

Embedded within the research team, this role designs and builds robust, scalable systems and architectures to translate cutting-edge agentic AI research into production-quality platforms. You’ll lead research-driven engineering, scale large-scale agent training infrastructures, and mentor researchers and engineers while collaborating across safety and LLM/VLM teams.

Location: London

Workplace: Hybrid

Employment Type: Full time

Job Function: Research & Scientific (R&D)

Key Responsibilities

•Design and implement new agents, proposing research directions that combine state-of-the-art RL with foundation models (LLMs/VLMs).
•Design, implement, and scale complex, high-performance systems for training large-scale agents including infrastructure, algorithms, reward models, and training environments.
•Collaborate with researchers and engineers to implement, test, and productionize new agent logics, learning algorithms, and system architectures.
•Create, manage, and scale large benchmarks and evaluation systems; own reliability, scalability, and observability of the research infrastructure.
•Mentor and guide other engineers and researchers; establish and enforce engineering standards, tooling, and best practices for code and research design.

Travel: Low travel

Key Requirements

•Senior Experience as a Staff, Principal, or Senior Engineer (or equivalent Research Scientist) in a Frontier AI Lab with a proven track record of leading complex, end-to-end AI/ML projects from conception to production.
•PhD (or equivalent research experience) in Machine Learning, Computer Science, or related field, preferably with a strong publication record (e.g., NeurIPS, ICML, ICLR).
•Deep theoretical and practical expertise in Agentic AI and proven experience building, scaling, and shipping solutions involving foundation models (LLMs/VLMs).
•Collaborative, high-impact communicator with ability to bridge research and engineering and to solve new engineering challenges at the frontier of agentic AI.
•Bonus: Practical experience applying reinforcement learning to systems built on LLMs; distributed systems or AWS; simulation environments for agent training; LLM training or fine-tuning; large-scale evaluation and benchmarking; agentic frameworks (LangChain, AutoGen, CrewAI, OpenAI SDK); system architecture, instrumentation, observability and monitoring.

Experience:AIMachine LearningResearchFoundation modelsRL

Education:PhD / Doctorate

Skills:CollaborationCommunicationMentorshipLeadershipTeamwork

Tech Stack:Reinforcement learningFoundation modelsLLMsVLMsDistributed systemsAWSLangChainOpenAI SDKSimulation environmentsLLM trainingBenchmarkingObservability

Company Brief

H Company

Develops agentic AI foundation models and deployable AI agents (e.g., Surfer H, Runner H) to automate web and enterprise tasks, improving productivity for large organisations through visual-language and planning capabilities.

Industry: AI & Machine Learning

Company Size: Medium (51 to 250 employees)

Growth: Early Stage Startup

Funding: Seed

Headquarters: Paris, France

Founded: 2023

Glassdoor: 2.5

Website LinkedIn Glassdoor

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H Company

3 months ago

Member of technical staff - Agent

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 1 day agoStatus: Live

Job Summary

Location: London

Workplace: Hybrid

Employment Type: Full time

Job Function: Research & Scientific (R&D)

Key Responsibilities

•Design and implement new agents, proposing research directions that combine state-of-the-art RL with foundation models (LLMs/VLMs).
•Design, implement, and scale complex, high-performance systems for training large-scale agents including infrastructure, algorithms, reward models, and training environments.
•Collaborate with researchers and engineers to implement, test, and productionize new agent logics, learning algorithms, and system architectures.
•Create, manage, and scale large benchmarks and evaluation systems; own reliability, scalability, and observability of the research infrastructure.
•Mentor and guide other engineers and researchers; establish and enforce engineering standards, tooling, and best practices for code and research design.

Travel: Low travel

Key Requirements

•Senior Experience as a Staff, Principal, or Senior Engineer (or equivalent Research Scientist) in a Frontier AI Lab with a proven track record of leading complex, end-to-end AI/ML projects from conception to production.
•PhD (or equivalent research experience) in Machine Learning, Computer Science, or related field, preferably with a strong publication record (e.g., NeurIPS, ICML, ICLR).
•Deep theoretical and practical expertise in Agentic AI and proven experience building, scaling, and shipping solutions involving foundation models (LLMs/VLMs).
•Collaborative, high-impact communicator with ability to bridge research and engineering and to solve new engineering challenges at the frontier of agentic AI.
•Bonus: Practical experience applying reinforcement learning to systems built on LLMs; distributed systems or AWS; simulation environments for agent training; LLM training or fine-tuning; large-scale evaluation and benchmarking; agentic frameworks (LangChain, AutoGen, CrewAI, OpenAI SDK); system architecture, instrumentation, observability and monitoring.

Experience:AIMachine LearningResearchFoundation modelsRL

Education:PhD / Doctorate

Skills:CollaborationCommunicationMentorshipLeadershipTeamwork

Tech Stack:Reinforcement learningFoundation modelsLLMsVLMsDistributed systemsAWSLangChainOpenAI SDKSimulation environmentsLLM trainingBenchmarkingObservability

Company Brief

H Company

Industry: AI & Machine Learning

Company Size: Medium (51 to 250 employees)

Growth: Early Stage Startup

Funding: Seed

Headquarters: Paris, France

Founded: 2023

Glassdoor: 2.5

Website LinkedIn Glassdoor