11 months ago
Remote, Norway or Oslo, NorwayMid Level
Responsibilities
- Build AI-powered features for classification, summarization, content understanding, recommendations, and conversational interfaces.
- Collaborate with backend, frontend, product, and data science teams to integrate AI into existing products.
- Improve targeting and personalization logic using data science, machine learning, and product knowledge.
- Develop evaluation methods to measure AI system usefulness, accuracy, and reliability.
- Optimize LLM inference for cost, latency, and quality through context engineering, caching, model selection, and batching.
- Operate RAG pipelines and improve retrieval through experimentation with embeddings, chunking strategies, and ranking algorithms.
- Deploy and operate reliable services in Kubernetes with support from infrastructure, CI/CD, monitoring, and platform practices.
Requirements
- M.Sc. in Computer Science, Mathematics, or a related field, or a proven track record delivering complex ML/AI systems in production.
- At least 3 years of software engineering experience, including meaningful experience building production ML or AI systems.
- Fluency in Python and strong software engineering fundamentals.
- Curiosity about data quality, evaluation, and real-world ML/AI system behavior.
- Hands-on experience with LLMs such as OpenAI, Anthropic, or similar, and coding agents such as Claude Code.
- Clear English communication and ability to work with product and engineering teams.
- Preferred experience with agentic AI frameworks, tool-use patterns, Docker, Kubernetes, CI/CD, observability, vector databases, embedding models, search and retrieval systems, applied NLP, Airflow or similar ML pipeline tooling, production model monitoring, and React.
Benefits
- Flexible working hours, competitive compensation, and benefits.
- Laptop of choice, including Windows or Mac.
- Modern office with dedicated seating.
- Phone plan and life insurance.
- Generous token usage budgets focused on coding agents.
- Applicants must already have authorization to work in the jurisdiction without sponsorship from Piano.
Tech Stack
Categories
About Piano
Piano builds a SaaS digital experience platform that combines analytics, subscription/paywall management, identity, and journey orchestration for publishers and consumer brands. Customers use Piano Analytics and subscription tools to segment audiences, personalize offers, and manage paid relationships across web and apps. Privately held and headquartered in Amsterdam, it serves global enterprises including the BBC, The Telegraph, Nikkei, and The Wall Street Journal.