Engineer II (ML / GenAI Platform (ML / GenAIOps)

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 looking for an Engineer II - ML / GenAI Platform (ML / GenAI Ops)  who will be the backbone of our AI tool development and deployment efforts. This role is ideal for someone who thrives at the intersection of data science, engineering, and cloud infrastructure, and is excited to help build scalable, maintainable, and automated systems from the ground up.

In this role, this position will work closely with data scientists, business stakeholders, and cloud engineers to transform prototypes into robust, production-ready tools and applications. The work will directly impact on how predictive analytics, GenAI solutions, and interactive dashboards are delivered to internal business leaders.

Key Responsibilities :

• Collaborate with data scientists to convert experimental ML and GenAI workflows into scalable, production-ready pipelines.
• Co-develop and maintain shared, version-controlled repositories with modular components.
• Design and manage CI / CD pipelines using Azure DevOps for deploying ML models and GenAI tools.
• Containerize applications using Docker and deploy them using cloud-native services.
• Automate deployment workflows and infrastructure setup using Terraform and schema management tools for Azure and Snowflake.
• Ensure smooth integration of model training, evaluation, and deployment stages across projects.
• Deploy and manage GenAI solutions including chatbots, RAG applications, and predictive analytics tools.
• Operationalize LLMs and GenAI agents, including prompt orchestration and chaining logic.
• Track model versions, prompt iterations, and performance metrics to support continuous improvement.
• Implement observability tools to monitor latency, token usage, hallucination rates, and user feedback.
• Ensure compliance with internal governance policies around data security and ethical AI.
• Set up alerting and rollback mechanisms to handle model or infrastructure failures.
• Participate in code reviews and knowledge sharing sessions.
• Participate in and plan / suggest improvement to the existing workflows that impact business and technical domains.

Educational qualification :

Technical skills :

Soft skills :