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

Donaldson is committed to solving the worlds 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:

• Bachelors or Masters 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 inPythonBash and scripting for automation & CI/CD tools.
• Hands-on experience withCI/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

Employment opportunities for positions in the United States may require use of information which is subject to the export control regulations of the United States. Hiring decisions for such positions are required by law to be made in compliance with these regulations. Applicants for employment opportunities in other countries must be able to meet the comparable export control requirements of that country and of the United States.

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Our policy is to provide equal employment opportunities to all qualified persons without regard to race gender color disability national origin age religion union affiliation sexual orientation veteran status citizenship gender identity and/or expression or other status protected by law.