MLOps Engineer (Entry-level / Intern)

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.