ML Ops Engineer

We are looking for an MLOps Engineer to join our team. In this role, you will bridge the gap between Data Science and Operations. We are not looking for a generalist software engineer; we need someone who has specifically applied DevOps principles to Machine Learning—building CI/CD pipelines for models, managing Kubernetes clusters for training/inference, and who speaks the language of Data Scientists (PyTorch, Tensors, GPUs).SatSure is a deep tech, decision Intelligence company that works primarily at the nexus of agriculture, infrastructure, and climate action, creating an impact for the other millions, focusing on the developing world. We want to make insights from Earth observation data accessible to all.Join us to be at the forefront of building a deep tech company from India that solves problems for the globe.Roles & ResponsibilitiesML Pipelines: Design and build CI/CD pipelines specifically for ML workflows (training triggers, model versioning, testing) using tools like Jenkins, Bitbucket, or GitHub Actions.Orchestration: Deploy, configure, and optimize Kubernetes clusters to support containerized deep learning applications (managing GPU resources, node scaling).Model Serving: Work with Data Scientists to containerize and deploy PyTorch models using Docker and serving frameworks (KServe, Nvidia Triton Inference Server).Infrastructure: Manage cloud infrastructure (AWS) for data processing and model storage (S3, ECR, IAM).GitOps: Implement GitOps practices to manage the lifecycle of both infrastructure and ML configurations.Monitoring: Implement monitoring for both system health (CPU/Memory) and Model Drift/Performance using tools like Prometheus, Grafana, or ELK.Automation: Automate repetitive tasks related to dataset management and environment setup using Python.

Functional understanding of Machine Learning/Deep Learning concepts and the PyTorchframework. Mandatory: Prior experience working with Kubernetes and CI/CD in a production environment. Bachelor's degree in Computer Science, IT, or a related field; non-IT degrees with relevant experience are also acceptable.