Arena

Full-stack Engineer

• Expand data structures and business logic to support new features
• Visualize feature performance and usage metrics through internal tooling and dashboards
• Own the full feature lifecycle—from technical scoping to deployment and iteration based on insights
• Identify and advocate for process improvements in development, testing, and deployment.
• Experiment with new tools and frameworks to enhance productivity and product capabilities

Software Engineer, Full Stack

Business Development Rep

• Own the Model Lab Relationships: Serve as the primary business lead for top global model labs, managing the relationship from research lead to procurement.
• Drive Revenue Expansion: Expand revenue across modalities (text, code, multimodal, vision, auto-eval) by aggressively aligning our eval programs with each lab’s training and research roadmaps.
• Strategic Enterprise Expansion: Identify and close select opportunities to bring LMArena’s eval capabilities to high-value enterprise accounts (e.g., Salesforce, IBM, ServiceNow) seeking to evaluate internal or vendor models.
• Secure Market Presence: Negotiate co-release and marketing rights for every major lab partnership to ensure LMArena retains mindshare as the industry standard.
• Lifecycle Management: Own contract renewals, upsells, and expansions, ensuring forward visibility into multi-quarter revenue commitments.
• Pipeline Hygiene: Maintain rigorous revenue forecasts that tie directly to delivery schedules, consumption pacing, and renewal cycles.
• Deal Architecture: Design and enforce pricing frameworks that balance predictability (committed contracts) with flexibility (usage-based consumption).
• Cross-Functional Alignment: Collaborate with Delivery and Product teams to ensure evaluation capacity, quality, and timing are aligned with customer expectations.
• New Product GTM: Ramp up on net new Eval or Data Products and build the strategy to sell them into existing and net new relationships.

Business Development Lead

Data Scientist

• Explore and analyze large, complex datasets to uncover patterns, biases, and causal relationships in model behavior and system performance.
• Formulate hypotheses about data quality, evaluation outcomes, and model performance — then design experiments to validate or refute them.
• Build reproducible analysis pipelines using Python, Pandas, NumPy, and Spark to process and interrogate large-scale data.
• Partner with ML researchers and engineers to design metrics and analyses that evaluate how models perform across domains, prompts, and tasks.
• Develop causal reasoning frameworks and statistical methods that help explain why models behave as they do — not just how well they perform.
• Communicate insights (for example, via blog posts) clearly to technical and non-technical partners, informing both research direction and infrastructure improvements.

General Counsel

• Come join our legal team to work on the most exciting commercial, intellectual property, and operational issues at the leading edge of AI.
• You will be the second member of the legal team and have an opportunity to advise across the business, but with a focus on enterprise sales, data licensing, IP transactions, and trademark and patent portfolio management.
• Drive Commercial Agreements: Lead the drafting, review, and negotiation of complex enterprise agreements, including Master Services Agreements (MSAs), Data Processing Agreements (DPAs), software licenses, vendor agreements, and strategic partnership contracts.
• Strategic IP Advice: Lead IP strategy for our product development and machine learning teams, including advising on open source and IP considerations with respect to AI model training.
• Build and scale our commercial legal processes, creating playbooks, standardizing templates, and implementing systems to support a high-growth sales organization. Build agents and internal software to support our operations, and procure cutting-edge legal tech tools that allow us to integrate home-grown and vendor-built software with ease.
• Support the management of Arena's worldwide IP portfolio including patents and trademarks; assist with patent prosecution, trademark registration, and enforcement.
• Provide counsel on machine learning, generative AI, and other technical areas, with the ability to engage effectively with technical teams on complex engineering and data evaluation issues.

Associate General Counsel, Commercial & IP

Analytics Engineer

• Own the design and implementation of analytics-ready data models, schemas, and tables in our data warehouse
• Build and maintain reliable data pipelines (batch and incremental) that transform raw event and vote data into standardized, trusted datasets
• Define and standardize core metrics used across product, research, and customer-facing evaluations
• Partner with product managers and researchers to translate evaluation questions into robust data models
• Develop and maintain dashboards, reports, and data artifacts used by internal teams and external partners
• Ensure data quality through testing, validation, monitoring, and documentation
• Orchestrate and schedule data workflows using Airflow or equivalent tools
• Optimize queries and pipelines to support large-scale analytical workloads
• Contribute to improving data discoverability, lineage, and documentation across the warehouse

Machine Learning Engineer

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

• Design and conduct experiments to evaluate AI model behavior across reasoning, style, robustness, and user preference dimensions.
• Develop new metrics, methodologies, and evaluation protocols that go beyond traditional benchmarks.
• Analyze large-scale human voting and interaction data to uncover insights into model performance and user preferences.
• Collaborate with engineers to implement and scale research findings into production systems.
• Prototype and test research ideas rapidly, balancing rigor with iteration speed.
• Author internal reports and external publications that contribute to the broader ML research community.
• Partner with model providers to shape evaluation questions and support responsible model testing.
• Contribute to the scientific integrity and transparency of the LMArena leaderboard and tools.

Machine Learning Scientist

• LMArena is looking for a Machine Learning Scientist to lead our open-source research.
• You'll design, run, and share new methods and experiments that reveal what makes models useful, trustworthy, and capable.
• You’ll be responsible for curating high-impact datasets, developing new methodology and reproducible benchmarks, and releasing code.
• Collaborate with engineers to implement and scale research findings into production systems.
• Analyze large-scale human voting and interaction data to uncover insights into model performance and user preferences.

Machine Learning Scientist – Open Source Lead

Security Engineer

• Own the product security vision for LMArena, ensuring security and trust are core to every stage of our product lifecycle.
• Design and implement platform-wide security features, including Sybil resistance, bot detection, reputation systems, and anti-abuse primitives.
• Lead threat modeling and security architecture reviews for new and existing product features.
• Collaborate with infrastructure and product engineering to design secure APIs, data flows, and identity systems that scale.
• Improve developer velocity by creating secure-by-default frameworks and tooling for internal teams.
• Partner with incident response to quickly assess, contain, and remediate security events, and lead deep postmortems to improve defenses.
• Stay ahead of the curve by monitoring emerging attack techniques and applying cutting-edge security research to our platform.
• Mentor engineers across the company on secure coding practices, architecture trade-offs, and operational security.

Product Security Engineer

Solutions Engineer

• Own 5–15 active model lab relationships as the day-to-day point of contact
• Partner directly with researchers and product teams to integrate models, run evals, and deliver high-quality results
• Drive consistent delivery across onboarding, data + product releases, co-launches, and unblock unexpected issues fast
• Be the “owner” of a key process improvement or automation (e.g., model onboarding flow, customer data insights, delivery tooling)
• Translate customer feedback and research direction into concrete product ideas and engineering work
• Work across the stack to ship pragmatic solutions that push the frontier for our customers
• Help expand strategic accounts through trust, execution, and sharp technical judgment

Product Solutions Engineer

• Build and maintain integrations across core systems, creating a unified data layer that eliminates manual work and keeps teams aligned.
• Design end-to-end workflows across the contract lifecycle: intake → pricing → engineering handoff → delivery → QA → invoicing.
• Automate dashboards and reporting for real-time visibility into account health, delivery progress, renewals, and bottlenecks.
• Own revenue reporting and forecasting infrastructure with clear visibility for leadership and Finance.
• Architect and deploy inbound and outbound pipeline systems — from lead capture and scoring to routing and conversion.
• Own the GTM and operational tech stack end-to-end.