Senior MLOps Engineer

Unum UK

. Design, build, maintain, and scale production ML pipelines and platforms .

Posted 10/19/2026full-timeUnited StatesSenior💰 $89,400 - $183,500 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and maintaining production ML pipelines and platforms, with a strong focus on CI/CD workflows, observability, and infrastructure management. Proficient in mentoring engineers and establishing engineering standards for operational excellence in machine learning systems.

Highest-signal resume keywords

Production ML Pipeline DesignCI/CD Workflow ImprovementMLOps ExperiencePython ProgrammingAWS Cloud Infrastructure

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Machine Learning Systems SupportInfrastructure as CodeModel DeploymentModel ServingMonitoring TechnologiesDockerKubernetesTerraformML Lifecycle TechnologiesLLM or Agentic AI Project Experience

Soft Skills

Strong Communication SkillsCollaboration Across TeamsMentoring EngineersInfluencing Technical Direction

Tools & Technologies

AWSDatabricksMLflowGitHub ActionsAWS CloudWatchDatabricks Lakehouse Monitoring

Industry Keywords

MLOpsGenAIAgentOpsObservabilityCost ManagementGuardrailsOperational Excellence

Tech Stack

Tools & technologies

AWSCloudDockerKubernetesPythonTerraform

About the role

Key responsibilities & impact

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

Requirements

What you’ll need

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
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
Experience with ML lifecycle and platform technologies
Experience building or maintaining CI/CD pipelines
Experience with observability and monitoring technologies
Strong communication and collaboration skills across data science and engineering teams
Ability to mentor engineers, influence technical direction, and establish engineering standards
Preferred: Databricks, MLflow, GitHub Actions, AWS CloudWatch, Databricks Lakehouse Monitoring, GenAI or agentic AI solutions, AI/agent observability, evaluation, tracing, versioning, cost management, guardrails, and ML platform ownership at scale

Benefits

Comp & perks

Onsite fitness facilities
Generous paid time off
Employee professional development programs
Healthcare benefits (health, vision, dental)
Insurance benefits (short- and long-term disability)
Performance-based incentive plans
401(k) retirement plan with employer match up to 5%
Additional 4.5% 401(k) contribution whether you contribute to the plan or not