Ml/Ai Engineer

Ml/Ai Engineer - Detalhes da Vaga. ● You''ll work close to the data, turning messy enterprise sources into features, models, and AI-powered applications that run reliably in production rather than living in a notebook. ●The client is a data and AI platform company that modernizes how energy and heavy-industry enterprises work with their data, migrating legacy systems onto Databricks and the lakehouse and then building intelligence on top of it. ● The work is hands-on and full-lifecycle: you''ll touch pipelines, models, and the services that put predictions in front of real users. ●This role suits someone who likes living at the seam between data engineering and ML. ● If you''ve shipped models that depend on real pipelines holding up, and you want to do that work on a clean Databricks stack instead of fighting infrastructure, you''ll feel at home here. ●What You''ll Do- Build, train, and validate ML models on Databricks, with real attention to evaluation, generalization, and where the model will actually be used- Engineer features and data transformations in Spark and SQL from enterprise sources that are rarely tidy- Stand up MLflow-based workflows for experiment tracking, model registry, and reproducible training runs- Deploy models as batch jobs or real-time endpoints, then keep them honest with monitoring for drift, latency, and cost- Partner with data engineers on the lakehouse layer so the data feeding your models is reliable and well-modeled- Bring LLM and retrieval techniques into the mix where they fit the problem, and skip them where they don''t- Apply solid engineering habits throughout: version control, testing, code review, CI/CDQualifications- 3 to 5+ years building ML or AI systems in production, with strong Python fundamentals- Hands-on experience with Databricks, including Spark and Delta Lake (Azure Databricks is a plus)- Comfort across the ML lifecycle: feature engineering, training, validation, deployment, and monitoring- Working knowledge of MLflow or a comparable experiment tracking and model registry tool- Strong SQL and a real understanding of how data pipelines feed models- Exposure to LLM-powered or retrieval-based applications, or genuine curiosity to grow into them- Professional working English, since collaboration happens across a distributed teamWhy Join UsYou''ll join a small, senior team that has been steadily building out a Databricks-based platform for demanding enterprise clients, where the data is complex and the standards for what ships are high. ● The work is remote and async-friendly, and your models won''t sit on a shelf; they go into systems people actually depend on. ●If you want ownership over real ML work on a clean, modern stack, with teammates who care about doing it right, this is a strong fit. ●To apply, click Apply on LinkedIn and visit eliosai. ●Com/browse-jobs. Requisitos para participar do processo. ● . O que oferecemos.