Company Description Betterdata is a leading provider of an AI Programmable Synthetic Data Platform that helps data & AI teams to share data safely and compliantly. By anonymizing sensitive real data into privacy-preserving synthetic data, our platform enables instant and secure data sharing globally while prioritizing data privacy. Visit our job openings at https://tinyurl.com/betterdatajobs. Role Description This is a full-time remote role for an Entry-level / Intern MLOps Engineer at Betterdata. The MLOps Engineer will be responsible for day-to-day tasks involving deploying machine learning models, managing pipelines, monitoring model performance, and ensuring smooth integration of data and ML systems. Key Responsibilities: Deploy and manage Kubernetes clusters and Docker containers for ML workloads Build and maintain automation using Jenkins, Argo Workflows, Argo Events, and Argo CD Write Bash and Python scripts to automate infrastructure and ML pipelines Work across cloud platforms (AWS, Azure, GCP) to configure and manage cloud-native components like: Kubernetes (AKs, EKS, GKE) Storage (e.g., S3, Blob, GCS) Compute (e.g., EC2, Azure VMs, GCE) Networking (e.g., VPC, Load Balancers) IAM and Secrets Management Monitor and troubleshoot infrastructure for ML pipelines Collaborate with the MLOps lead to explore and integrate new tools and practices Qualifications: Bash scripting Docker & Kubernetes Jenkins or similar CI/CD tools (e.g:Github actions) Python scripting One or more cloud platforms (AWS, Azure, GCP) Basic networking concepts Interest or experience in the Argo ecosystem (Workflows, Events, CD) Exposure to MLOps tools like MLflow, Airflow etc Experience deploying ML models or pipelines in cloud/on-premise air gapped environments Degree in Computer Science, Machine Learning, or related field. Exceptional analytical and problem-solving skills. Fast learner with a proactive mindset and eagerness to grow Clear communicator and effective collaborator Why Join Us: Join a team poised to make significant impacts in the synthetic data technology space, where your contributions will shape the future of the field. Real-world exposure to MLOps challenges and solutions. Our start-up environment offers the excitement of innovation and problem-solving, competitive compensation, opportunity to be converted and the chance to challenge and expand your skills at the intersection of data privacy and utility.