Middle AI / ML Engineer

Skyro is a rapidly expanding fintech company serving thousands of customers in the Philippines through our lending business. Our mission is to evolve into a full-fledged financial ecosystem, delivering cutting-edge solutions that make financial services more accessible, efficient, and secure for everyone.What you will do:Build AI applications end-to-end: design, prototype, and ship LLM features (chat, assistants, knowledge tools) from scratch.Design systems: create scalable, reliable architectures for data, inference, and integrations.Develop APIs: build and maintain REST/FastAPI services for AI features; ensure performance, security, and versioning.RAG pipelines: design and run retrieval-augmented generation with vector databases and chunking/embedding strategies; automate workflows with n8n.Agentic workflows: implement autonomous/assisted agents using frameworks like LangChain, LangGraph, AutoGen to orchestrate tools and multi-step tasks.Prompting & evaluation: manage prompt versioning, run LLM output evaluation, A/B tests, and guardrails to improve quality and safety.Model ops: deploy, monitor, and optimize LLM services in production;Chatbots for specific domains: build domain-aware chatbots with proper grounding, context windows, and conversation memory.Media generation (nice to have): prototype audio/video generation.Software engineering: write clean, tested Python; code reviews; documentation; contribute to best practices.Data & SQL: write efficient SQL for analytics/features and to validate model outputs.Collaborate: partner with product/design to scope features and deliver measurable outcomes.What you should have:Practical experience building and deploying ML/LLM applications in production.Python expertise and strong foundations in data structures/algorithms.System design experience for scalable services (caching, queues, rate limits, monitoring).API development: hands-on with REST and FastAPI (or similar).RAG experience: embeddings, chunking, retrieval, re-ranking, and evaluation.Prompt engineering and fine-tuning (when needed) with clear measurement of impact.MLOps/Prod: CI/CD, Docker; familiarity with Kubernetes is a plus.Software engineering fundamentals: testing, version control, code quality, deployment.SQL proficiency for feature work and data validation.Communication: able to work closely with product and engineering.English B2 - a tech interview will be in EnglishSpoken Russian is a plusWhat happens after you apply?We review applications on a rolling basis and aim to get back within 2–3 business days. If there’s a fit, we’ll reach out. If you don’t hear from us within 2–3 weeks – consider it a pass. Thanks for taking the time – we appreciate your interest. 🚀Collaboration NoticePlease note that the workday should start no later than 2 PM (GMT+8)/7 AM (CET) to ensure effective collaboration within our international team.