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Machine Learning Engineer

Machine Learning Engineer at LMArena

Location: SF Bay Area/Remote

Type: Full-Time

About the Role:

LMArena is seeking a Senior Machine Learning Engineer to help scale and strengthen the core infrastructure that powers real-world AI evaluation. You’ll play a foundational role in shaping how we build, deploy, and improve our model benchmarking systems, working across data pipelines, inference APIs, and new evaluation methodologies. This is an opportunity to apply your technical expertise to a platform trusted by millions, and to help define how cutting-edge AI is assessed in the wild.

As one of the first ML engineers on the team, you’ll partner closely with researchers, engineers, and product leadership to turn new ideas into reliable systems. You’ll help us move fast while staying rigorous, improving reproducibility, scaling up to new modalities, and deepening our ability to understand and compare frontier models.

Responsibilities:

  • Architect and build what will become our core modeling for data and evaluation products

  • Own the full stack data, model training, and eval pipelines

  • Help grow a culture of feedback and rapid product iteration as we build new features as a tight-nit team

  • Conduct research into state-of-the-art evaluation methods and contribute to the long-term vision for a centralized, scalable evaluation platform.

Who is LMArena?

Created by researchers from UC Berkeley’s SkyLab, LMArena is an open platform where everyone can easily access, explore and interact with the world’s leading AI models. By comparing them side by side and casting votes for the better response, the community helps shape a public leaderboard, making AI progress more transparent, and grounded in real-world usage.

Why Join Us?

Trusted by organizations like Google, OpenAI, Meta, xAI, and more, LMArena is rapidly becoming essential infrastructure for transparent, human-centered AI evaluation at scale. With over one million monthly users and growing developer adoption, our impact is helping guide the next generation of safe, aligned AI systems—grounded in open access and collective feedback.

Our work is regularly referenced by industry leaders pushing the frontier of safe and reliable AI. Sundar Pichai, Jeff Dean, Elon Musk, and Sam Altman.

  • High Impact: Your work will be used daily by the world’s most advanced AI labs.

  • Global Reach: Develop data infrastructure powering millions of real-world evaluations, influencing AI reliability across industries at the top-tier

  • Exceptional Team: We are a small team of top talent from Google, DeepMind, Discord, Vercel, UC Berkeley, and Stanford.

Requirements:

  • Strong programming skills with the ability to work across the stack in a typical recommendation system or LLM stack

  • Experience in deep learning, language models or reward model training

  • Experience in working with LLM for fine tuning, prompt engineering, function calling etc

  • Self-motivated with a willingness to take ownership of tasks

  • A passion for shipping quality products

  • 4+ years of industry experience or relevant projects

  • Solid understanding of statistics, and various tools and methodologies for evaluating uncertainty in a way that is specific to the given product being shipped

What we offer:

  • 210k - 250k + equity. Actual compensation will depend on job-related knowledge, skills, experience, and candidate location.

  • Competitive salary and meaningful equity

  • Comprehensive healthcare coverage (medical, dental, vision)

  • The opportunity to work on cutting-edge AI with a small, mission-driven team

  • A culture that values transparency, trust, and community impact

Come help build the space where anyone can explore and help shape the future of AI.

Average salary estimate

$230000 / YEARLY (est.)
min
max
$210000K
$250000K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

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EMPLOYMENT TYPE
Full-time, hybrid
DATE POSTED
June 14, 2025

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