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.
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
Collaborate with backend, product, and platform teams; contribute to the overall system architecture; write efficient, testable, secure, and documented code
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
Want to increase your chances? Please ensure your LinkedIn profile is complete, up to date, and accurately reflects your experience before submitting your application.
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.
United States
India