AI / Machine Learning Engineer

Role overview

Responsibilities

• check_circle Conduct research into emerging AI and Machine Learning methodologies to design, prototype, and develop innovative features for our product suite.
• check_circle Fine-tune Large Language Models (LLMs) on domain-specific data to enhance performance, accuracy, and relevance for targeted project use cases.
• check_circle Translate complex business and cybersecurity problems into viable AI-driven solutions, building robust algorithms from the ground up.
• check_circle Deploy, apply, and maintain machine learning models in a production environment using scalable, containerized deployments.
• check_circle Interact with our Data Lakehouse using Apache Spark to process large volumes of data and ensure clean, efficient data pipelines for model training and inference.
• check_circle Integrate AI tools, RAG pipelines, and customized models into internal systems using Python/Java to drive productivity and efficiency.
• check_circle Work closely with multidisciplinary teams to ensure that R&D outcomes are successfully integrated into the final product roadmap.

Basic qualifications

• Master’s degree in Computer Engineering (Engenharia Informática), Computer Science, or a related field.
• Proficiency in Python and/or Java.
• Proven experience building models with TensorFlow, PyTorch, and Scikit-learn, backed by a solid understanding of algorithms, data structures, and statistics.
• Hands-on experience developing and deploying applications using Docker.
• Ability to read, understand, and implement methodologies from academic or technical research papers into functional code.

Preferred qualifications

• Strong familiarity big data processing using Apache Spark.
• Experience working with Large Language Models (LLMs), including fine-tuning techniques (e.g., PEFT, LoRA), Natural Language Processing (NLP), Vector Databases, and building Retrieval-Augmented Generation (RAG) pipelines.