About the job

Donaldson is committed to solving the world's most complex filtration challenges. Together, we make cool things. As an established technology and innovation leader, we are continuously evolving to meet the filtration needs of our changing world. Join a culture of collaboration and innovation that matters and a chance to learn, effect change, and make meaningful contributions at work and in communities.

Role Overview:

We are seeking a Dev/MLOps Engineer to be the backbone of our AI tool development and deployment efforts. This role sits at the intersection of data science, engineering, and cloud infrastructure ideal for someone passionate about building scalable, automated, and production-grade AI systems.

You will collaborate with data scientists, business stakeholders, and cloud engineers to transform prototypes into reliable, high-performance applications. Your work will power predictive analytics, GenAI solutions, and interactive dashboards used by our business leaders.

Key Responsibilities

Work with data scientists to turn ML and GenAI experiments into scalable production pipelines.
Build and maintain shared code repositories and reusable components.
Design CI/CD pipelines in Azure DevOps to deploy models, APIs, and GenAI tools.
Containerize applications using Docker and deploy them using cloud-native services.
Automate infrastructure setup using Terraform and manage schemas in Azure and Snowflake.
Deploy and manage GenAI apps such as chatbots, RAG systems, and predictive tools.
Monitor model performance, token usage, and system reliability.
Set up alerts, rollback plans, and observability tools to ensure stability.
Take part in code reviews and suggest workflow improvements.

Required Skills

Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field.
2-3 years of experience in ML engineering, MLOps, platform engineering or DevOps role with exposure to Gen AI/ML workflows.
Technical Skills
Strong proficiency in Python, Bash, and scripting for automation & CI/CD tools.
Hands-on experience with CI/CD tools (Azure DevOps preferred)
Experience with Docker and cloud-native services (Azure & Snowflake preferred).
Soft Skills
Strong problem solving & debugging skills
Excellent communication & collaboration abilities
Willingness to learn, experiment & contribute to evolving practices

Why Join Us

Be part of a growing team shaping the future of internal AI tools and automation.
Work on impactful projects that directly support business decision-making.
Enjoy a culture that values innovation, ownership, and cross-functional collaboration.

DevOps/MLOps Engineer