Senior MLOps Engineer

Job Posting End Date: November 22

Our Fortune 500 company is driving a digital transformation and looking for forward-thinking innovators to disrupt how our industry thinks about and uses technology. As one of the world's leading employee benefits providers, we help millions of people gain affordable access to benefits that help them protect their families, their finances and their futures.

Are you an asker of questions, a solver of problems, and a challenger of the status quo? Our mission is to provide a differentiated customer experience and exceed the expectations people have of technology at any company — not just insurers. 

We are seeking individuals to join our team of talented IT professionals who share never-ending passion and an unwavering focus on our customer experience. Team members comfortable working in an agile, fast-paced, and delivery-focused environment thrive in our environment where we value an entrepreneurial spirit and those who challenge the status-quo.

Unum is changing, and we’re excited about what’s next. Join us.

General Summary:We’re looking for a hands-on Senior MLOps Engineer who has experience building and operating machine learning systems in production.
This is not primarily a data science/model-development role, and it is not a traditional DevOps position. We’re looking for someone who has personally worked across the production ML lifecycle, including CI/CD, model deployment and serving, monitoring, Kubernetes, cloud infrastructure, and Infrastructure as Code.
You’ll help maintain and scale our existing ML platform while building new capabilities across MLOps, GenAI, and AgentOps. You’ll work closely with data scientists and engineers and serve as a senior technical contributor who can help establish standards and mentor other engineers.
You may be a particularly strong fit if you are a software or DevOps engineer who moved into MLOps, or an ML engineer with strong production infrastructure experience. You are comfortable going beyond experimentation and can speak to ML systems you have personally deployed, monitored, troubleshot, and supported in production.

Job Specifications:

• Bachelor’s degree in Computer Science, Information Technology, Information Systems, a related field, or equivalent relevant work experience.

• 5+ years of relevant software engineering, DevOps, ML engineering, MLOps, or related experience
• Demonstrated hands-on production MLOps experience across CI/CD, model deployment, model serving, and monitoring
• Strong Python development skills
• Hands-on production experience with AWS
• Strong experience with Docker and Kubernetes
• Hands-on experience with Infrastructure as Code, such as Terraform
• Experience with an ML lifecycle platform such as MLflow or a comparable technology
• Experience supporting production ML systems, including troubleshooting, monitoring, reliability, and operational support
• Hands-on involvement with at least one LLM or agentic AI project, such as RAG, evaluation, tracing, monitoring, versioning, cost management, or guardrails
• Ability to mentor engineers, influence technical decisions, and work effectively across data science and engineering teams
  

Preferred, not required:

• Databricks
• Unity Catalog
• Databricks Jobs/Workflows
• Databricks Model Serving
• Databricks Lakehouse Monitoring
• GitHub Actions
• AWS CloudWatch
• Production AgentOps experience

Principal Duties and Responsibilities:

• Build, scale, and maintain production ML pipelines and platforms
• Develop CI/CD workflows for ML models, including automated testing, versioning, deployment, and rollback
• Build and operate infrastructure supporting real-time and batch model serving
• Implement monitoring and observability across model performance, system health, reliability, and production issues
• Develop cloud infrastructure using AWS and Infrastructure as Code
• Deploy and operate containerized ML workloads using Docker and Kubernetes
• Support ML lifecycle capabilities including experiment tracking, model registries, versioning, and production deployment
• Help expand MLOps capabilities into GenAI and AgentOps, including evaluation, tracing, monitoring, versioning, cost management, and guardrails
• Partner with data scientists and engineers to improve platform reliability, scalability, and developer experience
• Mentor engineers, contribute to design reviews, and help establish MLOps engineering standards
  

#LI-TS1

~IN1

Our company is built on helping individuals and families, and this starts with our employees. We want employees to maintain a positive balance, which is why we provide access to the benefits and resources they need to invest in themselves. From our onsite fitness facilities and generous paid time off to employee professional development programs, we are committed to helping employees live and work their best – both inside and outside the office.

Unum is an equal opportunity employer, considering all qualified applicants and employees for hiring, placement, and advancement, without regard to a person's race, color, religion, national origin, age, genetic information, military status, gender, sexual orientation, gender identity or expression, disability, or protected veteran status.

The base salary range for applicants for this position is listed below. Unless actual salary is indicated above in the job description, actual pay will be based on skill, geographical location and experience.

$89,400.00-$183,500.00

Additionally, Unum offers a portfolio of benefits and rewards that are competitive and comprehensive including healthcare benefits (health, vision, dental), insurance benefits (short & long-term disability), performance-based incentive plans, paid time off, and a 401(k) retirement plan with an employer match up to 5% and an additional 4.5% contribution whether you contribute to the plan or not.  All benefits are subject to the terms and conditions of individual Plans.

Company:

Unum