AI/ML Engineer

We are looking for an AI/ML Engineer to join our team and build and improve the intelligence layer of our platform. You will design and orchestrate AI workflows that combine live web research, LLMs, and machine learning models to generate insights. This is a hands-on engineering role - you will design prompts, build async pipelines, train and deploy ML models, and ship production features end to end. What You'll Do Design, build, and orchestrate AI workflows that combine live web search, LLM scoring, and structured reasoning pipelinesBuild and tune prompt systems for structured LLM outputs - scoring rubrics, reasoning generation, hallucination preventionTrain, evaluate, and improve ML/deep learning models for prediction tasks using structured dataDeploy ML models to production as inference endpoints/services, manage versioning and rollback, and continuously monitor model performance (drift, accuracy decay, data quality) - retraining and updating models as neededBuild async data collection pipelines that gather data from external sources in real timeMonitor LLM behavior in production using observability tooling and continuously improve prompt qualityDesign scoring systems that are explainable and consistentImprove data quality by building smart deduplication, classification, and validation logic What We're Looking For Strong Python skills - async/await, asyncio, production-quality codeExperience working with LLM APIs and prompt engineeringUnderstanding of ML/deep learning fundamentals - feature engineering, model training, evaluation, hyperparameter tuningExperience with gradient boosting models (e.g., CatBoost, XGBoost, LightGBM) for prediction tasksExperience with MLOps - deploying models to production, versioning, and monitoring model performance over timeExperience with web scraping and data extraction at scaleComfortable working with relational databases and async database driversStrong debugging skills - you can trace a bug through a multi-step async pipelineProduct sense - you understand that AI outputs need to be explainable and trustworthy to end users Nice to Have Experience with deep learning frameworks (e.g., PyTorch, TensorFlow)Experience fine-tuning and serving transformer-based modelsFamiliarity with RAG (Retrieval-Augmented Generation) systemsExperience with AWS RDS, S3, and SageMakerExperience with hyperparameter optimization frameworks