Job Description

Job Posted
Empty
Location
Full time
Remote
Internship#

Who are we looking for:

Suitable for recent grads, bootcamp completers or final-year semester with project experience. We currently do not support interns who are not graduating immediate after as this is meant to be a full time role.


We're looking for a motivated and fast-learning MLOps Entry Level / Final Semester Intern to support our engineering team. If you have hands-on familiarity with core DevOps and MLOps tools and are eager to learn and grow, this is a great opportunity to gain real-world experience in modern ML infrastructure.

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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

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Essential Skills and Qualifications:

High priority

Working knowledge of:


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

Good to have

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

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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.

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How to apply

Does this role sound like a good fit to you?

Submit your application

If the above does not work, you may email us your CV (pdf format) at jobs@betterdata.ai


Include the title of the role in your subject


Indicate your available start - end dates (DDMMYY - DDMMYY)


Send along links/supporting information that best showcase the relevant things you have built and done