Machine Learning Engineer

We are looking for talents who:

Have expertise in Computer Vision, Natural Language Processing (NLP), Generative AI, and Large Language Models (LLMs).

You will play a key role in developing and deploying machine learning solutions, focusing on Language Modeling, Retrieval Augmented Generation (RAG), Computer Vision and other large-scale applications.

Responsabilities:

· Design, implement, and deploy complex machine learning systems using traditional machine learning, deep learning, LLMs and foundation models.

· Develop and maintain python scripts for efficient data collection, preprocessing, as well as implementing APIs to seamlessly integrate AI models into existing systems.

· Manage the entire lifecycle of ML algorithms, including performance analysis and error correction.

· Continuously optimize models for performance, scalability and cost-effectiveness.

· Data collection and annotation for model training and evaluation, including automatic data synthesis.

· Design tests for machine learning algorithm effectiveness and performance monitoring.

· Stay updated with industry trends to incorporate cutting-edge techniques and tools into projects.

Requirements:

· Bachelor’s degree in computer science or related field.

· Over 3 years of experience in software development roles.

· Strong knowledge of popular machine learning techniques and algorithms.

· 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 image vector representations).

· Proficiency in Python, ML libraries (NumPy, Pandas, Scikit-Learn, Matplotlib), Deep Learning Frameworks (PyTorch, TensorFlow, Keras, HuggingFace), SQL, Poetry, and Git.

· Experience with API development and deployment using Docker and Kubernetes.

· Experience building Gen AI solutions using LLMs, including frameworks (LangChain, LlamaIndex), prompt engineering, fine-tuning, serving models, and RAG.

· Experience working with Docker, AWS (or GCP, Azure).

Additional Requirements: 

· Proficiency in English (B2 or higher)

· CV sent in English

· Good communication skills, proactive and eager to take on new challenges and learn new things.

· Team player with excellent interpersonal skills.

Nice to have:

· Experience with MLOps tools (e.g. AWS Sagemaker, MLFlow, KubeFlow).

· Familiarity with monitoring Gen AI solutions (LangSmith, Arize Phoenix).

· Experience with prompt-engineering or fine-tuning open source LLM (Mixtral 8x7b, LlaMA 3.1)

· AWS certifications (SAA-C03 or MLS-C01)

· Project Management experience (Leading big or small teams, managing client expectations)

· Experience with Agile methodologies (Scrum, Kanban, Lean).