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hirly last saw it live on 2 September 2026. Similar roles are on the live board.

Appfollow

Senior AI Engineer (Product Neuro Forge Team)

EU only (remote)

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Seniority
Senior
Work mode
Remote-friendly
First seen by hirly
1 Sept 2026

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the posting

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.

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Senior AI Engineer (Product Neuro Forge Team) at Appfollow — hirly