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Reflection Ai Jobs (NOW HIRING)

Advantest

AI Intern

Austin, TX

$15 - $20/hr

Design and analyze agentic workflows, including reflection, tool usage, and planning strategies * Develop and iterate on multi-step AI pipelines for task execution and reasoning

Dropzone AI

AI Research Engineer

$200K - $250K/yr

About Dropzone AI Dropzone's mission is to scale cybersecurity beyond human limits, and augment ... Design and implement advanced multi-step reasoning agents (tool use, planning, reflection, self ...

Advantest

AI Intern

Austin, TX · On-site

Design and analyze agentic workflows, including reflection, tool usage, and planning strategies * Develop and iterate on multi-step AI pipelines for task execution and reasoning Requirements:

Jahnel Group

Senior AI Engineer

Schenectady, NY · On-site +1

$120K - $160K/yr

Develop and implement agentic AI workflows (e.g., planning, reflection, tool use) using modern orchestration frameworks such as LangGraph. * Apply prompt engineering and retrieval-augmented ...

Jahnel Group

Senior AI Engineer

Schenectady, NY · On-site +1

$120K - $160K/yr

Develop and implement agentic AI workflows (e.g., planning, reflection, tool use) using modern orchestration frameworks such as LangGraph. * Apply prompt engineering and retrieval-augmented ...

Advantest

AI Intern

San Jose, CA · On-site

$17.75 - $23.50/hr

Experiment with prompting strategies, planning, reflection, and tool usage to improve reasoning ... AI workflows.

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How much do reflection ai jobs pay per year?

As of Jun 7, 2026, the average yearly pay for reflection ai in the United States is $78,076.00, according to ZipRecruiter salary data. Most workers in this role earn between $72,000.00 and $80,000.00 per year, depending on experience, location, and employer.
What cities are hiring for Reflection Ai jobs? Cities with the most Reflection Ai job openings:

Member of Technical Staff - Research Software Engineer

Reflection

San Francisco, CA • On-site

Full-time

Posted 28 days ago

Job description

Job Summary:
Reflection is on a mission to build open superintelligence and make it accessible to all. The role involves bridging the gap between research and production by designing and optimizing the core infrastructure behind frontier AI models, focusing on scalable training systems and large-scale data pipelines.
Responsibilities:
• Designing and optimizing large-scale training loops and data pipelines.
• Implementing state-of-the-art techniques and ensuring they are numerically stable and computationally efficient.
• Building internal tooling for launching, monitoring, and reproducing complex experiments.
• Diagnosing deep bottlenecks across the training stack (GPU memory issues, communication overhead, dataloader stalls).
• Translating research prototypes into reusable, production-grade infrastructure.
Qualifications:
Required:
• Strong software engineer who speaks the language of machine learning.
• Deep experience in at least one of the following: Distributed Training & Inference or Data Infrastructure.
• Enjoy working at the boundary between machine learning algorithms, distributed systems, and high-performance computing.
• Care deeply about performance, numerical stability, and reproducibility.
• Thrive in high-agency environments and enjoy solving hard technical problems.
Preferred:
• May not have a PhD, but knows how to implement a research paper.
Company:
Reflection is an AI lab building frontier open weight models. Our team previously built frontier LLMs at labs like DeepMind, OpenAI, and Anthropic. Founded in , the company is headquartered in New York, NY, US, , with a team of 51-200 employees. The company is currently Growth Stage.

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