Backend Engineer (ML Platform)

As a Backend Engineer (ML Platform), you will design, implement, and maintain scalable machine learning platforms and data pipelines that enable seamless deployment, scaling, and monitoring of models in production. You will set up monitoring for deployed models and track key metrics to ensure reliability and performance. You will apply software engineering best practices within the context of machine learning and collaborate with ML engineers to maintain model performance in production while integrating ML systems into the broader application stack. You will accelerate ML development, evaluation, and integration by automating workflows, tools, and processes to enhance collaboration and efficiency. Proficiency in Python and backend API design (e.g., FastAPI, Django) and hands-on experience with Docker, Kubernetes, and cloud platforms are essential. Nice-to-have skills include cloud platforms, ML frameworks (PyTorch, TensorFlow), MLOps tools (Kubeflow, MLflow, TFX), monitoring and logging tools (Prometheus, Grafana), and data engineering concepts (ETL pipelines, data lakes, data warehouses).