Senior Machine Learning Engineer

Stack

Responsibilities

• ▹Take part in the whole AI lifecycle: business problem understanding, data exploration and preparation, model development and training, production deployment and continuous monitoring
• ▹Design and build automated data and model pipelines using Apache Airflow, Kubeflow and MLflow, and help define scalable ML architectures on Azure, AWS and GCP
• ▹Work on projects ranging from traditional ML algorithms and optimization to generative AI: LLMs, Transformers, RAG systems, model fine-tuning and autonomous AI agents
• ▹Use Azure Databricks, Azure ML, AWS SageMaker, Google Vertex AI, OpenAI, Anthropic Claude, Hugging Face, LangChain and vector databases (Pinecone, Weaviate)
• ▹Implement MLOps and AIOps methodologies, with monitoring, data drift and model decay detection and automatic retraining strategies
• ▹Advanced feature engineering, hyperparameter tuning, performance optimization and continuous experimentation
• ▹Mentor teams, share knowledge and set ML excellence standards
• ▹Work directly with clients to understand business needs and turn them into technical AI solutions with measurable impact

Requirements

• ▹Technical degree in Computer Engineering, Telecommunications, Mathematics, Physics, Statistics or similar
• ▹End-to-end ML model development: from data exploration and feature engineering to training, validation and optimization
• ▹Practical experience deploying and maintaining models in production with monitoring and continuous retraining
• ▹Command of Python, scikit-learn, XGBoost, TensorFlow/PyTorch and Pandas, and experience deploying models on AWS, Azure or GCP
• ▹Real experience building production ML pipelines using Docker, Kubernetes, Airflow, MLflow or similar
• ▹Consulting mindset: client orientation, problem solving and working in dynamic environments
• ▹Ability to communicate in both English and Spanish for international projects

Nice to have

• ▹Generative AI experience: LLMs, fine-tuning, prompt engineering, OpenAI API, LangChain, vector databases
• ▹Experience designing scalable data architectures (data lakes, lakehouses, feature stores)
• ▹Certifications: AWS Certified ML Specialty, Google Professional ML Engineer, Azure AI Engineer or similar

Soft skills

What we offer

• ▹Permanent contract
• ▹Fully remote, hybrid or office, your choice
• ▹Intensive working hours in July and August and on Fridays
• ▹Salary according to education and experience
• ▹Financial support for remote work
• ▹Training, official certifications (AWS, Google, Azure), conferences and courses
• ▹Salary reviews and a clear career plan based on achievements
• ▹Multicultural teams

About the company

SDG Group is a global consultancy 100% specialized in data and artificial intelligence, with over 200 AI experts. It has built over 100 AI solutions running in production for 70+ clients in banking, retail, energy and healthcare, with 50+ proprietary accelerators and the SDG iLabs innovation lab.