San Jose, California, United StatesFull TimeEntry-level128k–256k USDPosted Today
The Applied Machine Learning Ark team combines system engineering and machine learning to develop and operate Large Language Model (LLM) service platforms that offer businesses Model-as-a-Service (MaaS) solutions, serving both large model providers and downstream users. The US team drives the design, development, and operation of MaaS solutions across the US and international markets outside mainland China. We are building full-stack, end-to-end solutions spanning text and multimodal LLM algorithms, LLM training/fine-tuning/inference frameworks, prompt engineering, model alignment, and intelligent agent systems. Beyond model serving, we operate large-scale log analytics pipelines that process massive volumes of invocation logs from text models, multimodal models, and agent systems — extracting usage patterns, quality signals, and actionable insights to inform model improvement, system optimization, and product decisions through continuous, data-driven feedback loops. We are actively seeking talented engineers and researchers specializing in Large Language Models and AI Agent systems to join our dynamic team.
We are looking for talented individuals to join our team. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth.
Successful candidates must be able to commit to an onboarding date by the end of the year. Please state your availability and graduation date clearly in your resume.
Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply. The application limit is applicable to our Company and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early.
Responsibilities:
- Design evaluation systems for LLM-based agents, covering task success, tool use, reasoning quality, and reliability.
- Build benchmarks and automated judging pipelines, combining rule-based checks, model-based judging, and human review, etc.
- Analyze agent execution traces and user feedback to identify failure patterns and turn them into concrete system improvements.
- Support the closed loop from experience to capability, and work with research, platform, and product teams to bring methods into production.
The base salary range for this position in the selected city is $128000 - $256000 annually.
We are looking for talented individuals to join our team. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth.
Successful candidates must be able to commit to an onboarding date by the end of the year. Please state your availability and graduation date clearly in your resume.
Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply. The application limit is applicable to our Company and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early.
Responsibilities:
- Design evaluation systems for LLM-based agents, covering task success, tool use, reasoning quality, and reliability.
- Build benchmarks and automated judging pipelines, combining rule-based checks, model-based judging, and human review, etc.
- Analyze agent execution traces and user feedback to identify failure patterns and turn them into concrete system improvements.
- Support the closed loop from experience to capability, and work with research, platform, and product teams to bring methods into production.
The base salary range for this position in the selected city is $128000 - $256000 annually.