AI Engineer

Requirements

• A solid grounding in machine learning fundamentals, including probabilistic modeling and deep neural networks
• Demonstrated track record in prompt engineering and context engineering using top-tier LLMs—e.g., OpenAI GPT models, Anthropic Claude, Google Gemini
• Experience delivering AI-first capabilities in customer-facing products—driving value through features users directly interact with
• Comfortable translating and communication complex technical concepts for non-technical stakeholders in user-facing documentation or demos
• Education + Experience:
  • Option A: Bachelor’s or Master’s degree in Computer Science, Software Engineering, or related STEM field plus ~3 years of professional AI/ML experience
  • Option B: No formal degree, ~6 years of self-taught or industry experience demonstrating equivalent proficiency

Nice-to-Have (Bonus)

• Experience with vector databases, RAG pipelines, LangChain, or agent frameworks
• Background in multi-modal AI (e.g., text, image, voice) or long-context handling, reflecting advanced LLM use cases
• Hands-on familiarity with ML frameworks like PyTorch, TensorFlow, or Hugging Face Transformers
• Prior work in MLOps, cloud infrastructure (AWS, GCP, Azure), or AI governance

What You'll Be Doing

• Design, develop, and ship AI-driven capabilities—including agents, intelligent assistants, context-aware prediction, and generative AI—that enhance Miro’s customer experience, from ideation to delivery
• Execute end-to-end ML projects: from conceptualizing use cases to prototyping, training, evaluating, and deploying models into production
• Engineer high-performing AI workflows leveraging off-the-shelf large language models (OpenAI, Anthropic Claude, Google Gemini, etc.), prompt engineering, retrieval-augmented generation (RAG), and generative techniques—ensuring reliability, scalability, and maintainability
• Collaborate cross-functionally with product managers, designers, engineers, and researchers to translate business goals into AI solutions, and to iterate rapidly through feedback and experimentation
• Champion best practices in AI system development—including evaluations, reproducibility, MLOps, CI/CD, observability, and version control—aligned with ethical AI and responsible development principles
• Measure and optimize AI performance, establishing benchmarks for outcomes like user engagement, model accuracy, latency, error rate, and drift
• Stay ahead of the curve by evaluating emerging AI tools, frameworks, and techniques—and advocating for their application across Miro

Perks and Benefits

• Competitive equity package
• Lunch, snacks, and drinks provided in the office
• Wellbeing benefit and WFH equipment allowance
• Annual learning and development allowance to grow your skills and career
• Opportunity to work for a globally diverse team