Our client is looking for a hands-on Full Stack AI Engineer who can take full ownership of an AI use case from concept to production. You'll work across the entire stack: from architecting analytics infrastructure, to building robust data pipelines, to developing and deploying advanced models. You'll curate high-quality datasets, engineer features, and create AI systems capable of handling complex workflows and adapting to user context.
Data Preparation and Curation
Si sus habilidades, experiencia y cualificaciones coinciden con las de esta descripción del puesto, no demore su solicitud.
Prepare, clean, and curate high-quality datasets for modeling. You'll also design and maintain a feature store to ensure consistent, reliable data availability for training and inference.
● Build Robust Data & ML Pipelines
Develop and maintain end-to-end data and machine learning pipelines—from ingestion to deployment and monitoring. This includes building analytics infrastructure using reusable dbt models and designing scalable workflows with Airflow.
● Take a hands-on role in model design, training, and evaluation. You'll explore and prototype solutions using a range of neural architectures, including but not limited to LLMs, ensuring performance, reproducibility, and reliability.
● This includes graph construction, entity linking, and hybrid scoring strategies.
● Experience delivering complete AI components—from planning and modeling to deployment, monitoring, and iteration.
● Strong Python skills and deep familiarity with ML frameworks such as Scikit-Learn, TensorFlow, PyTorch, and Hugging Face. MLOps & Data Engineering Proficiency
MLflow, ZenML), dbt modeling, and working with cloud data warehouses or data lakes.
● Pipeline & Data Skills
Experience building and scheduling pipelines in Airflow. Familiarity with modern data stacks such as Kafka, Spark, and cloud warehouses (BigQuery, Redshift, Snowflake). xqysrnh Experience developing frameworks for assessing model quality, reliability, hallucination detection, prompt regression, safety scoring, or multi-hop reasoning.