Full-Stack AI Engineer

• Own the Pipeline: Build and maintain the "plumbing" (Airflow, dbt) and the "orchesteration" (MLflow, ZenML) of our AI products.
• Research & Experiment: Apply a research-oriented mindset to solve complex problems like multi-hop reasoning, model quantization for edge devices, and advanced retrieval.
• Evaluate & Refine: Don't just ship it-verify it. You'll build frameworks to detect hallucinations, measure regression, and ensure our models are safe and explainable.

Do you have experience in SQL?, Do you have a Master's degree?, We need a Full-Stack AI Engineer who is as comfortable with mathematical modeling and research as they are with deploying production-grade code. You will own the entire lifecycle: from choosing the right architecture to building the data pipelines that feed it., We are looking for a practitioner with deep foundations. You should have:

• Strong ML Fundamentals: Proven experience solving problems with traditional ML (XGBoost, LightGBM) and deep feature engineering.
• Deep Learning Expertise: Hands-on experience with CNNs, RNNs, or Transformers. You understand what happens inside the model, not just how to call an API.
• Research Background: A strong plus. You can read a paper and implement the findings.
• The Full-Stack Mindset: Proficiency in Python and ML frameworks (PyTorch, TensorFlow, Scikit-Learn), plus experience with the modern data stack (SQL, dbt, Airflow).

• Competitive compensation aligned with experience
• Flexible working setup
• Time and budget for learning and development
• Real ownership over features and technical decisions
• A collaborative, low ego engineering environment
• A product used by millions of professionals worldwide

Hiring Stages

• Application Review
• Technical Interview with Coding Challenge
• Exec Interview
• HR Interview (incl. Bryq Personality Assessment)
• Final Steps

Doodle is a B2B SaaS platform used by millions of professionals to coordinate meetings and collaboration across teams and companies. We are expanding from a scheduling product into a broader productivity and coordination platform, which creates meaningful technical challenges at scale.