Machine Learning Engineer - AI Applications
On-site · Rio Grande do Sul, Brazil
Job Summary
Machine Learning Engineer - AI Applications focused role developing and deploying ML and GenAI models. Responsibilities include designing and implementing ML/GenAI pipelines, training and validating models with appropriate metrics, deploying models to production with scalable and reliable systems, and collaborating with CI/CD, research, and engineering teams to advance techniques such as retrieval-augmented generation (RAG), embeddings, and vector databases. Requires hands-on experience with ML/DL frameworks, Python, Azure, LangChain, OpenAI API, and production deployment, along with strong analytical and collaborative skills.
Required Qualifications
- Bachelor’s or Graduate Degree in Computer Science, Statistics, Mathematics, Data Science, Artificial Intelligence, or a related discipline — or equivalent professional experience demonstrating strong competence in machine learning and generative AI
- Typically possesses 4–7 years of experience in software development, machine learning, generative AI, statistical modeling, or related fields. Candidates with an advanced degree may have 3–5 years of relevant experience, including hands-on work with large language models (LLMs), multimodal GenAI systems, and model deployment in production environments
- Experience with large language models (LLMs), multimodal GenAI systems, and model deployment in production environments
- Knowledge of Agile Methodology, Azure Cloud, LangChain, OpenAI API, Vector Databases (e.g., FAISS, AI Search, ElasticSearch), PyTorch, TensorFlow, Scikit-learn, Hugging Face Transformers, API integration, and CI/CD practices
- Strong programming in Python; familiarity with ML/DL frameworks; experience building and deploying ML/GenAI pipelines; ability to optimize hyperparameters and monitor models in production
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