Machine Learning Operations Engineer - Data, AI

Overview

It's an exciting time to join Fisher Investments! We're continuing to invest in the future of our firm's technology and information security. As our business grows internationally, the need for resilient, scalable AI solutions has never been greater. We are looking for an Machine Learning Operations Engineer responsible for deploying machine learning models and ensuring their efficient, secure, and scalable operation.

The Opportunity:

As a Machine Learning Operations Engineer, you will design, implement, and maintain the systems that bridge the gap between machine learning development deployment. You will work with data scientists, data engineers, and platform teams to ensure models are monitored, versioned, governed, and continuously improved. You will report to the Vice President, Technology Innovation.

The Day-to-Day:

• Build, maintain, and improve Machine Learning pipelines for training, testing, deployment, and monitoring
• Develop CI/CD workflows tailored for ML environments, including model versioning and reproducibility
• Implement monitoring systems for model drift, performance, and reliability
• Automate retraining and deployment workflows using Kubernetes, Docker, and cloud services
• Collaborate with security and governance teams to ensure compliance with internal and external regulations
• Partner with data scientists to translate experiments into production-ready pipelines
• Contribute to the evolution of scalable AI platforms using Azure Machine Learning, NVIDIA NIMs, and NeMo services

• 10+ years experience developing data-related solutions and software
• 5+ years of experience with Machine Learning Operations, DevOps, or related disciplines
• 5+ years of proficient experience with Python, strong experience in ML frameworks (TensorFlow, PyTorch, Scikit-learn)
• Hands-on expertise with Kubernetes, Docker, and CI/CD tools (Azure DevOps, Jenkins, GitHub Actions)
• Experience with monitoring tools (Prometheus, Grafana, MLflow, Weights & Biases)
• Deep knowledge of cloud-native AI services, especially Microsoft Azure AI
• Practical experience with NVIDIA NIMs and NeMo services for deployment and fine-tuning of foundation models
• Familiarity with model governance, audit, and compliance frameworks
• Bachelor's degree in Computer Science, Data Science, or equivalent work experience

• $175,000 - $215,000 base salary per year in the state of WA. New hires should expect to start at the lower end of the range depending on experience
• Eligible for a discretionary bonus based on firm and individual performance

• 100% paid medical, dental and vision premiums for you and your qualifying dependents
• A 50% 401(k) match, up to the IRS maximum
• 20 days of PTO, plus 10 paid holidays
• Family Support programs including 8 week Paid Primary Caregiver Leave, $10,000 fertility, family forming, and hormonal health assistance, and back-up child, adult, and elder care
• This is an in-office role. Based on your role, tenure, and performance eligibility you may have the opportunity to participate in our hybrid work from home program.
• This program is subject to change.