← Back

Romain Zimmer

ML/AI Engineer — Paris, France

linkedin.com/in/romainzimmer   ·   hi@romainzimmer.com

Summary

ML/AI engineer with 7+ years building ML and AI systems, from spiking neural networks and surrogate-gradient training methods to production-scale ML pipelines. Deep interest in AI algorithms and systems — model architectures, training methods, and infrastructure — alongside hands-on experience taking ML from research to deployment. Currently cofounder/CTO of a product observability platform for AI agents.

Experience

• Cofounded and lead technology for correl8, a product observability platform that turns AI agent conversations into structured product signals (observations, sentiment, grouped issues).
• Designed agentic processing pipelines: an LLM-based ingestion pipeline (span classification, async issue digest, tag matching) and the Correl8 Assistant, an in-app conversational agent, plus background agents for autonomous analysis.
• Built MCP and REST integrations enabling third-party agents (LangChain, Pydantic AI, OpenAI Agents SDK) to post observations and conduct in-conversation research studies.
• Own full technical architecture and product direction as CTO.

• Hired to design and build a discount optimization system from scratch, enabling retailers to reduce waste and boost profits.
• Built and maintained data pipelines using DBT and Snowflake, and ML workflows using Metaflow.
• Developed predictive models for discount elasticity and a decision engine for optimal discounting.
• Developed an internal experimentation framework and ran in-store A/B tests with proven significant impact across multiple retailers.

• Delivered scalable ML infrastructure and CI/CD solutions.
• Refactored a Python codebase, implemented integration tests, and migrated a system from GCP to AWS Serverless.
• Deployed Triton Inference Server on AWS SageMaker and built Slack bots for ML validation tasks.

• Received funding via Inria Startup Studio to build Sievable, a machine learning-powered collaborative search engine.
• Created a scalable, deep learning-based search engine platform with user contributions and blockchain-backed incentives (token on Solana).
• Designed and deployed a full MLOps pipeline handling data ingestion, model training, embedding updates, and deployment.

• Conducted R&D on generative models for speech synthesis.
• Developed a Python library for benchmarking ML pipelines on ARM processors.

• Developed Spiking Neural Networks (SNNs) for audio analysis and modeled them using RNNs trained with surrogate gradient methods in PyTorch.

Research & Side Projects

• Binaml — long-running research project exploring alternatives to current neural network architectures and backpropagation, focused on binary representation learning; written in Rust.
• Teannamon — tea brand with our own, in-house-built AI shopping assistant that recommends tea to customers online; long-term vision of personalized tea on demand.

Education