Machine Learning Engineering
Hace 2 días
España
Preply
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As a category-defining company, we’re shaping what the future of learning looks like at global scale.
Every Preply lesson sparks change, fuels ambition, and drives progress that matters. Joining Preply means helping define the future of education at global scale, and building something that truly matters for millions of people, every day. Build and maintain ML pipelines for training, evaluation, and deployment using tools like Databricks, MLFlow, Airflow, DBT, Sagemaker, Tecton Support AI scientist creating reproducible, containerized model training environments (on-demand and scheduled), and manage compute at scale (e.g., Define and implement observability and alerting for ML systems (model drift, data quality, feature coverage, etc.) Design and scale data ingestion and feature transformation flows using batch (e.g., Spark/BigQuery) and streaming (Kafka or equivalent) Contribute to internal Python libraries and platform tooling that accelerate experimentation and deployment for all model teams Proven experience designing and deploying ML systems in production (5+ years in relevant roles) Proficiency in Python and SQL, and orchestration tools (Airflow, Kubeflow, Dagster, etc.) Experience with modern cloud platforms (preferably GCP or AWS), Kubernetes, and CI/CD workflows Understanding of ML model lifecycles: training, validation, deployment, and monitoring Strong DevOps practices: Git, IaC (Terraform), logging/observability, containerization (Docker/K8s) Ability to work independently with ML Scientists and mentor peers in reliability, testing, and delivery. Exposure to LLM serving, vector databases, or GenAI-powered product flows com, Learning & Development budget and time off for your self-development; A competitive financial package with equity, leave allowance and health insurance; Keep perfecting
- To create an outstanding customer experience, we focus on simplicity, smoothness, and enjoyment, continually perfecting it as every detail matters. Growth mindset
- We proactively seek growth opportunities and believe today's best performance becomes tomorrow's starting point. Raise the bar
- We raise our performance standards continuously, alongside each new hire and promotion. Challenge, disagree and commit
- We value open and candid communication, even when we don’t fully agree. We believe that the presence of different opinions and viewpoints is a key ingredient for our success as a multicultural Ed-Tech company. Senior Machine Learning Platform/Ops Engineer
• Madrid, Spain #
Every Preply lesson sparks change, fuels ambition, and drives progress that matters. Joining Preply means helping define the future of education at global scale, and building something that truly matters for millions of people, every day. Build and maintain ML pipelines for training, evaluation, and deployment using tools like Databricks, MLFlow, Airflow, DBT, Sagemaker, Tecton Support AI scientist creating reproducible, containerized model training environments (on-demand and scheduled), and manage compute at scale (e.g., Define and implement observability and alerting for ML systems (model drift, data quality, feature coverage, etc.) Design and scale data ingestion and feature transformation flows using batch (e.g., Spark/BigQuery) and streaming (Kafka or equivalent) Contribute to internal Python libraries and platform tooling that accelerate experimentation and deployment for all model teams Proven experience designing and deploying ML systems in production (5+ years in relevant roles) Proficiency in Python and SQL, and orchestration tools (Airflow, Kubeflow, Dagster, etc.) Experience with modern cloud platforms (preferably GCP or AWS), Kubernetes, and CI/CD workflows Understanding of ML model lifecycles: training, validation, deployment, and monitoring Strong DevOps practices: Git, IaC (Terraform), logging/observability, containerization (Docker/K8s) Ability to work independently with ML Scientists and mentor peers in reliability, testing, and delivery. Exposure to LLM serving, vector databases, or GenAI-powered product flows com, Learning & Development budget and time off for your self-development; A competitive financial package with equity, leave allowance and health insurance; Keep perfecting
- To create an outstanding customer experience, we focus on simplicity, smoothness, and enjoyment, continually perfecting it as every detail matters. Growth mindset
- We proactively seek growth opportunities and believe today's best performance becomes tomorrow's starting point. Raise the bar
- We raise our performance standards continuously, alongside each new hire and promotion. Challenge, disagree and commit
- We value open and candid communication, even when we don’t fully agree. We believe that the presence of different opinions and viewpoints is a key ingredient for our success as a multicultural Ed-Tech company. Senior Machine Learning Platform/Ops Engineer
• Madrid, Spain #