Senior MLOps Engineer

• Bachelor's degree in Computer Science, Information Technology, Information Systems, a related field, or equivalent relevant work experience.
• 5+ years of experience in software engineering, DevOps, ML engineering, MLOps, or a related discipline, with demonstrated experience supporting machine learning systems in production.
• Strong Python programming skills and software engineering fundamentals.
• Hands-on production MLOps experience across CI/CD, model deployment, model serving, and monitoring.
• Hands-on experience with AWS and cloud-based infrastructure.
• Strong experience with Docker and Kubernetes.
• Experience with Infrastructure as Code, such as Terraform.
• Hands-on experience contributing to at least one LLM or agentic AI project, such as a proof of concept, pilot, or production implementation. Relevant experience may include RAG, evaluation, versioning, monitoring, tracing, cost management, or guardrails.
• Experience with ML lifecycle and platform technologies. Databricks and MLflow are preferred, although comparable production MLOps tools and platforms will be considered.
• Experience building or maintaining CI/CD pipelines. Experience with GitHub Actions is preferred.
• Experience with observability and monitoring technologies. AWS CloudWatch and Databricks Lakehouse Monitoring experience is preferred.
• Strong communication and collaboration skills with the ability to work effectively across data science and engineering teams.
• Ability to mentor other engineers, influence technical direction, and help establish engineering standards without formal people-management responsibility.

• Hands-on experience with Databricks, including capabilities such as Unity Catalog, Jobs/Workflows, Model Serving, and Lakehouse Monitoring.
• Experience with MLflow for ML lifecycle management.
• Experience supporting GenAI or agentic AI solutions beyond initial experimentation.
• Experience with AI/agent observability, evaluation, tracing, versioning, cost management, or guardrails.
• Background as a software/DevOps engineer who transitioned into MLOps, or an ML engineer with strong infrastructure engineering experience.
• Experience owning or improving an ML platform at scale.

• Design, build, maintain, and scale production ML pipelines and platforms supporting model deployment, serving, monitoring, and lifecycle management.
• Build and improve CI/CD workflows for ML models, including automated testing, versioning, deployment, and release processes.
• Develop and operate scalable infrastructure supporting real-time and batch model inference.
• Implement monitoring and observability for ML systems, including model performance, system health, reliability, and operational issues.
• Help expand MLOps capabilities into GenAI and AgentOps, including areas such as evaluation, versioning, monitoring, tracing, cost management, and guardrails.
• Maintain and improve infrastructure using Infrastructure as Code, including Terraform or comparable technologies.
• Support ML lifecycle capabilities such as experiment tracking, model registries, model serving, and ML workflow orchestration.
• Partner with data scientists and engineers to improve the reliability, scalability, and maintainability of production ML solutions.
• Drive continuous improvements to deployment processes, monitoring, platform reliability, and developer experience.
• Establish and promote engineering standards around reproducibility, security, governance, and operational excellence.
• Mentor other engineers, contribute to technical design decisions, and help establish MLOps engineering standards across teams.

#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