Arena Machine Learning Engineer at Arena builds and scales core infrastructure for real-world AI evaluation. The role involves architecting data and evaluation products and owning full stack data, model training, and evaluation pipelines.
Responsibilities
Arena Intelligence is seeking a 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.
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.
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
Qualification
Experience in deep learning
Required
Strong programming skills across stack in recommendation system or LLM stack
Experience in deep learning, language models or reward model training
Experience working with LLM for fine tuning, prompt engineering, function calling
Self-motivated with willingness to take ownership
4+ years of industry experience or relevant project experience
