ZAM Network is a multi-faceted company based in the United States. We specialize in building engaged gaming communities through its three core pillars of marketing, creative services and user research. ZAM operates one of the largest gaming networks in the world including the #1 community for World of Warcraft, Wowhead. 

Wowhead was created with one sole intent: providing World of Warcraft players with tools and information to make their gameplay more enjoyable. All staff members are passionate fans of World of Warcraft, which helps us keep abreast of the most important features other players are interested in! We pride ourselves on our comprehensive database with helpful user comments, popular tools like the Dressing Room and Flying Tracker, lightning-fast datamining to uncover the latest test realm updates, and detailed guides written by professional players on all popular WoW topics including classes, collections, secrets, and raids. We’ve branched out to cover the Diablo franchise and are planning our next stage of growth.

We are currently seeking a Reverse Engineer with extensive data mining experience to join our team as an independent contractor. This is not an entry level role and you will be working to extract both static and runtime game data for World of Warcraft to help Wowhead to expand our current tools to aid our community of gamers. This position is a full-time remote as you will collaborate with the entire Wowhead team as we work together to deliver world-class products to our fans.

Key Responsibilities

• Manage development of the Wowhead Studio application, to facilitate datamined assets of creatures, characters, and other in-game objects
• Extract game data and game assets required to build tools to support our products and services.
• Maintain Wowhead’s model tools using the site’s WebGL model viewers. TypeScript-based standard viewer used in most of Wowhead website.
• Use C++ web assembly-based viewer that is faster with accurate lighting, for various World of Warcraft Player Housing pages.
• Use JavaScript-based Three.js model viewer.
• Maintain comprehensive technical documentation on game data (contents, formats, change history), data mining tools and processes employed, and anything else related to the role.
• Communicate consistently, clearly, and efficiently all assigned task progress, blockers, or any other role-related issues in a prompt and professional manner on a regular basis.

Experience and Technical Requirements

• Previous hands-on experience doing data mining work on World of Warcraft and/or Diablo IV. This is not a “learn as you go” type of role; we operate in a fast paced, highly competitive, and challenging environment.
• Comprehensive understanding using various programming languages (such as C++, Python, C#, TypeScript and JS) in order to choose the best tool for the job.
• Understanding of various debugging, reverse engineering, and custom made tools to accomplish assigned tasks.
• Ability to read and comprehend x86/x64 assembly language, such as via IDA as this role is not solely a “file format” data mining role.
• Strong communication skills in English, both written and verbal, with the ability to convey information clearly and effectively.
• A collaborative mindset; ability to collaborate remotely and coordinate with stakeholders across different time zones.
• Professionalism, reliability, and a commitment to delivering high quality work utilizing your analytical and problem-solving skills.
• Being experienced in Blizzard games will make it easier to understand project requirements and the consumer side.

At JetBrains, code is our passion. Ever since we started, back in 2000, we've been striving to make the strongest, most effective developer tools on earth. Today, AI-powered coding agents are becoming a core part of how developers write Kotlin – and we want to make sure they write it well.

The Kotlin AI Value Stream team is responsible for how AI agents understand, generate, and improve Kotlin code across all platforms: Android, Kotlin Multiplatform, server-side, web, desktop, and others. We build the evaluation infrastructure, error analysis tools, and post-training pipelines that measure and improve agent behavior on real Kotlin developer tasks.

As a Research Engineer on this team, you'll own the end-to-end loop: Analyze how agents fail on Kotlin → build evals that capture those failures → research and implement methods to fix them → measure the improvement. Your work will directly shape how millions of developers experience Kotlin through AI coding agents.

As part of our team, you will:

Build tools for agentic error analysis

• Design and implement tooling to systematically capture, classify, and analyse errors that AI coding agents make when generating Kotlin code.
• Build observability pipelines over agentic traces – mining patterns from agent sessions in JetBrains IDEs, Junie, Claude Code, Cursor, and other coding agents.

Build evaluation pipelines

• Design, implement, and maintain evaluation pipelines that measure Kotlin code generation quality across dimensions, including correctness, idiomaticity, build success, framework usage, and test coverage.
• Build simulation environments where coding agents can be measured on realistic Kotlin developer tasks – from greenfield KMP projects and Gradle dependency management to migrating Spring applications from Java to Kotlin.
• Own evaluation infrastructure: metrics, experiment tracking, automated regression checks, and reproducible benchmarking.

Research methods for improving agent and model behavior on Kotlin

• Experiment with post-training techniques (SFT, DPO, GRPO) to improve how models handle Kotlin-specific patterns, idioms, and frameworks.
• Investigate context engineering approaches: CLAUDE.md/AGENTS.md files, compiler-as-verifier feedback loops, Kotlin LSP integration, and MCP-based tooling.
• Run experiments to measure impact: A/B comparisons, benchmark suites, and before/after analyses on real codebases.
• Collaborate with model providers (Anthropic, OpenAI, and Google) to translate Kotlin-specific findings into model improvements.

Build public Kotlin benchmarks

• Design and build open-source benchmarks that measure AI coding agent performance on Kotlin tasks and eventually become the standard reference for the ecosystem.
• Create task datasets covering the breadth of Kotlin usage: the server side (Spring, Ktor), multiplatform projects (KMP), build systems (Gradle), Android, library development, and others.
• Include both mined real-world tasks and carefully designed synthetic tasks that test specific Kotlin capabilities.
• Maintain and evolve benchmarks as models improve, ensuring they remain challenging, relevant, and contamination-resistant.

We'll be happy to have you on board if you have:

• Hands-on experience building evaluation or analysis pipelines for LLMs or AI coding agents in a research or production setting.
• Strong Python engineering skills (at least three years), with the ability to write clean, maintainable code in data-heavy and ML-adjacent codebases.
• Experience with data analysis at scale: querying large datasets (SQL/Athena), building data pipelines, and performing statistical analysis of experimental results.
• The ability to own projects end to end – from identifying a problem in agent traces to designing an eval, running experiments, and shipping a fix.
• A product-aware mindset: You care about how agents are actually used by developers and can translate real failure modes into evaluation and training work.
• Familiarity with Kotlin or a strong willingness to develop deep Kotlin expertise (you'll be living in Kotlin codebases daily).

Our ideal candidate would also have experience with:

• Post-training LLMs: SFT, RLHF, DPO, GRPO – either hands-on training or designing the data and reward pipelines that feed into training.
• Modern deep learning frameworks (PyTorch) and LLM training stacks (TRL, verl, Megatron, or similar).
• AI agent development: tool-using agents, multi-step coding workflows, agentic frameworks.
• Evaluation frameworks and tools: Inspect AI, Promptfoo, LM-evaluation-harness, or custom eval pipelines.
• Experiment tracking and observability: Weights & Biases, MLflow, Langfuse, or similar.
• The Kotlin ecosystem: Android, Gradle, KMP, Spring, Ktor – with an understanding of the developer workflows that agents need to support.
• Contributing to or maintaining open-source projects, especially benchmarks or evaluation tools.

Don't check every box? That's okay – if you're excited about this work and bring strong fundamentals, we'd love to hear from you. We're happy to talk and provide the training you need to grow into the role.

Why join JetBrains? 

• Strong base salary. We offer competitive pay that reflects your skills and experience.
• Flexible work location. Enjoy the freedom to work from home or from the office.
• Remote work. Spend up to 30 days per year working remotely from abroad.
• Extra time off. More days to relax, recharge, and do the things you love.
• Medical insurance allowance. Enjoy peace of mind for you and your family
• Learning and development opportunities. Access to conferences, courses, and language classes.
• Relocation support. We help make your move as smooth and stress-free as possible. 
• Language classes. Pick up the local language or sharpen your English skills.
• Fuel your day. Enjoy a hot meal or receive a lunch allowance on workdays.
• Mental health support. To help you feel your best, we provide easy access to professional mental health services.
• Sports benefit. Enjoy an on-site gym or sports club stipend.
• Internal events. Join company-wide celebrations and team gatherings.

*Some benefits may vary depending on location.

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