Machine Learning Engineer

Responsabilities:

• Design, implement, and deploy complex Machine Learning systems using traditional Machine Learning, Deep Learning, LLMs, and foundational models.
• Develop and maintain Python scripts for data collection and preprocessing, as well as for implementing APIs that integrate AI models into existing systems.
• Manage the entire lifecycle of Machine Learning algorithms, including performance analysis and bug fixing.
• Design tests to evaluate the effectiveness of Machine Learning algorithms and monitor their performance.
• Stay updated with industry trends to incorporate cutting-edge techniques and tools into projects.

Requirements:

• 3+ years of experience with Machine Learning
• Proficiency in Python, Machine Learning libraries such as NumPy, Pandas, Scikit-learn, Matplotlib, with a preference for Poetry
• Proficiency with Deep Learning frameworks such as PyTorch, TensorFlow, Keras, HuggingFace; SQL and GIT
• Experience building Machine Learning solutions (including GenAI options, LLMs, frameworks like LangChain and LlamaIndex, prompt engineering, RAG)
• Degree in Computer Science, Computing Engineering, or related field

Nice to have:

• AWS certifications (SAA-C03 or MLS-C01)
• Experience with NLP tasks (e.g., text classification, named entity recognition, language modeling, and vector representations)
• Experience with Computer Vision tasks (e.g., image classification, object detection, and vector representations of images)
• Experience developing and deploying APIs using Docker and Kubernetes
• Experience working with Docker and cloud services such as AWS (or GCP, Azure)
• Conversational English proficiency