高级AI工程师(产品Neuro Forge团队)
Senior AI Engineer (Product Neuro Forge Team)
AppFollow 是一款应用评论管理和 ASO 平台。
AppFollow 是一款应用评论管理和 ASO 平台。我们的主要目标是简化应用开发人员、产品经理、营销团队、客户支持等日常任务。AppFollow 帮助您收集和管理您的应用和游戏数据,提高应用平均评分,改善应用商店排名,以及提升应用用户忠诚度。
评分和评论是我们核心数据,AI 是我们将其转化为客户价值的方式,帮助他们通过用户反馈自动化常规工作并节省时间:反馈分类、评论摘要、AI 生成回复、语义搜索、异常检测和对话洞察。
这个全远程职位是 Senior AI Engineer,将从研究和原型设计到生产端到端地推动这些功能。您将与商业 LLM 和开源模型一起工作,构建训练和评估流程,并推出由 ML 驱动的功能,这些功能将被全球的应用和游戏团队,以及任何处理数字用户反馈的人使用。这本质上是一个应用工程岗位:您的模型不会停留在笔记本中。与我们的后端团队合作,您还将开发围绕这些功能的产品功能、服务和 API。
关于该职位
- 全程负责 AI/ML 功能:研究、原型、生产、监控和迭代
- 在评分和评论数据基础上设计和构建 LLM 驱动的功能:反馈分类、摘要、回复生成、语义搜索、异常检测、对话和代理场景
- 使用商业 LLM API(OpenAI、Anthropic、Google)以及开源模型(Llama、Mistral、Qwen 等):模型选择、适配、微调和部署
- 构建和维护模型训练、微调和质量评估的流程:数据集、指标、离线评估、LLM 作为评判者、A/B 测试
- 开发 RAG 和语义搜索功能:嵌入、向量存储、检索质量
- 优化 LLM 推理在生产环境中的质量和成本
- 跟踪 NLP/LLM 的最新进展,运行实验和 POC,并将有前景的成果转化为产品功能
- 开发和优化 AppFollow 产品功能,超越 ML:对核心数据实体(应用、评论、评分)的服务和内部及公共 API
- 将新功能集成到现有系统中,包括遗留服务,并与平台团队合作部署到各种环境并确保平稳运行
查看英文原文
AppFollow is an App review management and ASO platform.
AppFollow is an app review management and ASO platform. Our main goal is to ease the everyday routines of app developers, product managers, marketing teams, customer support, etc. AppFollow helps you gather and manage your apps and games data, increase app average rating, improve app store rankings, and app user loyalty.
Ratings and reviews are our core data, and AI is how we turn them into value for our customers, helping them automate routine work with user feedback and save time: feedback categorization, review summarization, AI-generated replies, semantic search, anomaly detection, and conversational insights.
This fully remote role is for a Senior AI Engineer who will drive these capabilities end-to-end, from research and prototyping to production. You'll work with both commercial LLMs and open-source models, build training and evaluation pipelines, and ship ML-powered features used worldwide by app and game teams, as well as anyone working with digital user feedback. This is an applied engineering role at heart: your models won't stay in notebooks. Together with our backend team, you'll also develop the product functionality, services, and APIs around them.
About the Role
- Own AI/ML features end-to-end: research, prototype, production, monitoring and iteration
- Design and build LLM-powered features on top of reviews and ratings data: feedback categorization, summarization, reply generation, semantic search, anomaly detection, conversational and agentic scenarios
- Work with commercial LLM APIs (OpenAI, Anthropic, Google) as well as open-source models (Llama, Mistral, Qwen, etc.): model selection, adaptation, fine-tuning, and deployment
- Build and maintain pipelines for model training, fine-tuning, and quality evaluation: datasets, metrics, offline evals, LLM-as-a-judge, A/B tests
- Develop RAG and semantic search capabilities: embeddings, vector storage, retrieval quality
- Optimize quality, latency, and cost of LLM inference in production
- Track state-of-the-art in NLP/LLM, run experiments and POCs, and turn the promising ones into product features
- Develop and optimize AppFollow product functionality beyond ML: services and internal and public APIs to core data entities (apps, reviews, ratings)
- Integrate new features with the existing system, including legacy services, and collaborate with the Platform team to deploy to various environments and ensure smooth operation
- Contribute with other developers to the overall system architecture; design, build, and document an efficient, testable, reliable, secure, and scalable codebase
About you
- 5+ years of software development experience; strong production Python (asyncio)
- 3+ years of hands-on ML/NLP experience with models shipped to production
- Practical experience with LLMs: prompt engineering, RAG, fine-tuning open-source models (LoRA/PEFT), working with both commercial APIs and self-hosted models
- Experience building model quality evaluation processes: metrics, eval datasets and pipelines, A/B testing
- Confidence with the PyTorch and Hugging Face ecosystem (transformers, datasets, PEFT)
- Proficiency in FastAPI for API development
- Strong SQL skills (MySQL or PostgreSQL), experience with ORM frameworks (preferably SQLAlchemy)
- Experience with unit testing (pytest)
- Upper-intermediate English or higher
It would be nice to have
- Experience serving open-source LLMs in production (vLLM, TGI, Triton) and working with GPU infrastructure
- Experience with vector databases (e.g. pgvector)
- Experience with agentic and orchestration frameworks (LangChain, LangGraph) and eval/observability tooling (MLflow, Langfuse)
- Experience with data processing pipelines and automation (e.g. Airflow, Prefect)
- Experience with cloud-based services (AWS), NoSQL databases (MongoDB), message brokers (RabbitMQ, Kafka)
- Classical ML/NLP background (text classification, clustering, topic modeling)
- Open-source contributions, publications, or pet ML projects you're proud of
Benefits we offer
- Full-time remote job. Though you're always welcome to spend time with us in monthly All hands in our hubs: Helsinki, Belgrade, Tbilisi, Batumi, Yerevan
- Paid Vacation and Sick leaves. Take the time you need to stay motivated, charged, and balanced. By prior agreement, you can have days off for special occasions
- Generous social benefits package including health insurance, equipment reimbursement, home office moderation bonus, and many more
- Stock options bonus according to the employee stock ownership plan
- You'll have executive-level visibility into how the company is run and performing. We are always ready to provide dedicated support and fast-track your onboarding, including giving you the tools you need to be successful.
The biggest benefit is our awesome AppFollow team. We're a team of open-minded and friendly high-skilled professionals that enjoy creating a great product, growing together, and supporting each other.
Jump on the board!
Hiring process
- HR screening interview — 15 min
- Backend Technical interview — 90 min
- ML Technical interview — 90 min
- Culture fit interview — 60 min
- Recommendations check
Expected timeline: 2–4 weeks from application to offer.
Hint
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How To Recognise And Avoid Employment Scams
We’ve noticed an increase in fake job postings and fake job offers aimed at gathering personal information. Be aware that all official AppFollow recruitment emails come exclusively from an @appfollow.io domain. Our interviews are conducted either over video calls or in person; we never conduct interviews via text or chat. If you’re unsure about the legitimacy of a job offer or opportunity from AppFollow, please reach out directly to us at people@appfollow.io for verification.