ML/AI Engineer

The Role

We'relooking for an ML/AI Engineerwho enjoys turning real-world data into useful product solutions. You'lljoin our Data Science team and work across the full lifecycle: prototyping, evaluating, shipping, and operating ML and AI features across Piano's platform. This is not a single-product role. You'llmove between LLM-powered content understanding, personalization and targeting, intelligent customer workflows, and the agent systems underpinning a new generation of Piano products.

You'llhelp build agentic products that reason overPiano's analytics, audience, and subscription data and take real actionson behalf of our customers. You'lldevelop new ML and AI capabilities, from LLM-based classification to classical ML models for personalization. And you'llhelp keep our existing production ML solutions healthy - models that serve hundreds of millions of users and are essential for our customers' businesses.

Beyond the technical scope, we'rehiring for how you think. The engineers who will do their best work here are the ones who care about feeding AI systemsthe right information, validatingwhat those systems produce, and optimizingfor quality, cost, and latency.

What You'll Do

• Design and build agent systems that power new Piano products - tool calling, multi-step orchestration, memory and context management, and the integrations that let agents act safely on customer data

• Build guardrails and human-in-the-loop patterns so agents can take real actions on customer accounts

• Maintainand improve existing ML pipelines, model training workflows, and inference services to keep them stable and performant

• Build and improve classical ML models behind personalization and targeting

• Investigate and resolve production issues when they arise - understanding the problem by analyzing logs, model inputs and outputs, identifyingroot causes, and shipping enhancements that continuously improve how our ML systems perform

• Collaborate with data scientists, ML/AI engineers, product managers, and other teams across the company to deliver ML/AI solutions that solve real customer problems
• Deliverclean, tested, well-documented Python codeand uphold good engineering practices (Git workflows, code reviews, CI/CD)

What We're Looking For

Must-have

• M.Sc. inComputer Science, Mathematics, Statistics, Data Science, or a related field

• 3+ years of professional experience as an ML Engineer,AI Engineer,Data Scientist, or in a similar applied ML rolewith meaningful time building production ML or AI systems

• Fluency in Python and strong software engineering fundamentals, including Git and modern collaborative development workflows

• Solid understanding of core ML concepts - algorithms, evaluation, and model behavior - and the judgement to know when a classical model beats an LLM

• Experience with Docker, Kubernetes, cloud platforms (AWS/GCP), CI/CD, and observability tooling (logging, metrics, monitoring)

• Hands-on experience building with LLM APIs (OpenAI, Anthropic, or similar), including prompt and context engineering, structured outputs, and tool/function calling

• Hands-on experience with coding agents such as Claude Code

• Strong analytical and debugging skills, with a structured approach to problem-solving in unfamiliar systems

• Ability to communicate clearly in English and work with product and engineering teams

Nice-to-have

• Experience with agentic AI frameworks, orchestration, and tool-use patterns (Claude Agents SDK, PydanticAI, or similar)

• Experience with MCP-writing servers, or wiring agents to internal tools and data sources

• Experience with LLM observability and evaluation tooling - we use Langfuse, but experience with LangSmith, Braintrust, or similar is fine

• Experience with optimizingLLMinference for cost, latency, and quality through context engineering, model selection, caching, and batching

• Experience with ML pipeline tooling (Airflow or similar)

• Exposure to A/B testing infrastructure for ML and AI features

Applicants must have authorization to work in this jurisdiction without sponsorship from Piano.

Nice-to-have

• Experience with agentic AI frameworks, orchestration, and tool-use patterns (Claude Agents SDK, Pydantic AI, or similar)

• Experience with MCP - writing servers, or wiring agents to internal tools and data sources

• Experience with LLM observability and evaluation tooling - we use Langfuse, but experience with LangSmith, Braintrust, or similar is fine

• Experience with optimizing LLM inference for cost, latency, and quality through context engineering, model selection, caching, and batching

• Experience with ML pipeline tooling (Airflow or similar)

• Exposure to A/B testing infrastructure for ML and AI features

Applicants must have authorization to work in this jurisdiction without sponsorship from Piano.

Nice-to-have

• Experience with agentic AI frameworks, orchestration, and tool-use patterns (Claude Agents SDK, Pydantic AI, or similar)

• Experience with MCP - writing servers, or wiring agents to internal tools and data sources

• Experience with LLM observability and evaluation tooling - we use Langfuse, but experience with LangSmith, Braintrust, or similar is fine

• Experience with optimizing LLM inference for cost, latency, and quality through context engineering, model selection, caching, and batching

• Experience with ML pipeline tooling (Airflow or similar)

• Exposure to A/B testing infrastructure for ML and AI features

Applicants must have authorization to work in this jurisdiction without sponsorship from Piano.

Nice-to-have

• Experience with agentic AI frameworks, orchestration, and tool-use patterns (Claude Agents SDK, Pydantic AI, or similar)

• Experience with MCP - writing servers, or wiring agents to internal tools and data sources

• Experience with LLM observability and evaluation tooling - we use Langfuse, but experience with LangSmith, Braintrust, or similar is fine

• Experience with optimizing LLM inference for cost, latency, and quality through context engineering, model selection, caching, and batching

• Experience with ML pipeline tooling (Airflow or similar)

• Exposure to A/B testing infrastructure for ML and AI features

Applicants must have authorization to work in this jurisdiction without sponsorship from Piano.

Nice-to-have

• Experience with agentic AI frameworks, orchestration, and tool-use patterns (Claude Agents SDK, Pydantic AI, or similar)

• Experience with MCP - writing servers, or wiring agents to internal tools and data sources

• Experience with LLM observability and evaluation tooling - we use Langfuse, but experience with LangSmith, Braintrust, or similar is fine

• Experience with optimizing LLM inference for cost, latency, and quality through context engineering, model selection, caching, and batching

• Experience with ML pipeline tooling (Airflow or similar)

• Exposure to A/B testing infrastructure for ML and AI features

Applicants must have authorization to work in this jurisdiction without sponsorship from Piano.

Nice-to-have

• Experience with agentic AI frameworks, orchestration, and tool-use patterns (Claude Agents SDK, Pydantic AI, or similar)

• Experience with MCP - writing servers, or wiring agents to internal tools and data sources

• Experience with LLM observability and evaluation tooling - we use Langfuse, but experience with LangSmith, Braintrust, or similar is fine

• Experience with optimizing LLM inference for cost, latency, and quality through context engineering, model selection, caching, and batching

• Experience with ML pipeline tooling (Airflow or similar)

• Exposure to A/B testing infrastructure for ML and AI features

Applicants must have authorization to work in this jurisdiction without sponsorship from Piano.