ML/AI Engineer
At a glance
Mid-level AI Engineering role at piano. Bratislava · full-time.
Pay not stated AI Engineering salary
aimlroles summary, based on the employer's posting.
What you'll do
- Build agents that use tools, coordinate multi-step tasks, retain context, and act safely on customer data
- Add safeguards and human review so agents can make changes to customer accounts responsibly
- Keep production ML pipelines, training workflows, and inference services reliable and improve their performance
- Develop personalization and targeting models, then investigate production problems using logs and model behavior
- Ship tested, documented Python code while working with data science, product, and engineering colleagues
What you bring
- A master's degree in computer science, mathematics, statistics, data science, or a related discipline
- At least three years in applied ML or a similar role, including substantial work on production ML or AI systems
- Strong Python and software engineering skills, plus practical use of Git and collaborative development practices
- Experience with Docker, Kubernetes, AWS or GCP, CI/CD, and tools for logs, metrics, or monitoring
- Hands-on work with LLM APIs, prompt and context design, structured responses, tool calling, and coding agents
Who this fits
This role suits a mid-level engineer who wants to build both agent-based features and classical ML systems, and stay involved from prototyping through production support. You’ll work across data science, product, and engineering teams. The setup is hybrid, based in Bratislava, and applicants need existing work authorization in the jurisdiction without Piano sponsorship.
From the employer
The Role
We're looking for an ML/AI Engineer who enjoys turning real-world data into useful product solutions. You'll join 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'll move between LLM-powered content understanding, personalization and targeting, intelligent customer workflows, and the agent systems underpinning a new generation of Piano products.
You'll help build agentic products that reason over Piano's analytics, audience, and subscription data and take real actions on behalf of our customers. You'll develop new ML and AI capabilities, from LLM-based classification to classical ML models for personalization. And you'll help 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're hiring for how you think. The engineers who will do their best work here are the ones who care about feeding AI systems the right information, validating what those systems produce, and optimizing for 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
- Maintain and 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, identifying root 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
- Deliver clean, tested, well-documented Python code and uphold good engineering practices (Git workflows, code reviews, CI/CD)
What We're Looking For
Must-have
- M.Sc. in Computer 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 role with 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, 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
Why Piano
- You'll work in a cross-functional team infusing Piano products with AI and ML, with direct impact on how notable global media brands serve hundreds of millions of users
- You'll build agent systems that ship into Piano products
- You'll get unusual breadth: production ML at scale, new AI feature development, and greenfield agentic products, in one role
- You'll have real influence over the tech stack and the freedom to choose your tools
- You'll collaborate with highly skilled peers across data science, ML engineering, and product, in a company that moves fast and values craftsmanship
- Generous token usage budgets with a focus on getting value from coding agents
- Flexible working hours, competitive compensation, and benefits
- Laptop of your choice
- Modern office with dedicated seating
- Hybrid work setup
Applicants must have authorization to work in this jurisdiction without sponsorship from Piano.