MLOps Engineer

EPAM Systems; Brasil; Remote; BRL 120,000 - 180,000; Full time

Benefits offered by this job

Healthcare benefits

Paid time off

LinkedIn Learning access

Career development opportunities

Global career opportunities

Volunteer opportunities

Employee Groups

Job summary

EPAM Systems seeks an MLOps Engineer to join a major data analytics project in real estate. You will help transform systems to the cloud, streamline ML model production, and improve cost efficiency, availability, and reliability through architectural improvements.

You will design data solutions, build automated ML pipelines, deploy and monitor models in production, and work with Google Vertex AI, Kubeflow, and Kubernetes on GCP. This role is on-site with global teamwork.

Qualifications

• 2+ years of experience in an MLOps or similar role.
• Proficiency in Python.
• Expertise in Google Vertex AI and Google Vertex AI Pipelines.
• Skills in monitoring ML models in production.
• Familiarity with Jenkins and Docker.
• English proficiency at B1+ level or above.
• Nice to have AI Solution Engineering background and Prompt Engineering.
• Knowledge of Google Cloud Platform, Ansible, and Terraform.
• Familiarity with Kubeflow and Kubernetes.
• Proficiency in Groovy and JetBrains PyCharm.

Responsibilities

• Understand and manage the ML systems lifecycle.
• Frame ML problems based on business objectives.
• Design data solutions tailored to the problem at hand.
• Perform data preparation and processing.
• Conduct model training and experimentation.
• Build and automate ML pipelines.
• Deploy models to the production system.
• Monitor, optimize, and maintain models in production.

Skills

Python

ML pipelines design

Model monitoring

Data processing

Jenkins

Groovy

PyCharm

Tools

Docker

Kubeflow

Kubernetes

Terraform

Ansible

Jenkins

Job description

We are seeking an MLOps Engineer to join a major company that aggregates broad and deep property data and generates analytics informing smart decision-making and property-level insights relied upon by hundreds of thousands of users in the real estate industry.In this role, you will help transform systems to the cloud, enabling cost optimization, improved availability and reliability through architectural improvements, and enhanced analytics with better TTM. You will focus on streamlining the process of taking machine learning models to production, as well as maintaining and monitoring them.ResponsibilitiesUnderstand and manage the ML systems lifecycleFrame ML problems based on business objectivesDesign data solutions tailored to the problem at handPerform data preparation and processingConduct model training and experimentationBuild and automate ML pipelinesDeploy models to the production systemMonitor, optimize, and maintain models in productionRequirements2+ years of experience in an MLOps or similar roleProficiency in PythonExpertise in Google Vertex AI and Google Vertex AI PipelinesSkills in monitoring ML models in productionFamiliarity with Jenkins and DockerEnglish proficiency at B1+ level or aboveNice to haveBackground in AI Solution Engineering and Prompt EngineeringKnowledge of Agentic SDKs and Google Agent Development KitExperience with Google Cloud Platform, Ansible, and TerraformFamiliarity with Kubeflow and KubernetesProficiency in Groovy and JetBrains PyCharmWe offerInternational projects with top brandsWork with global teams of highly skilled, diverse peersHealthcare benefitsEmployee financial programsPaid time off and sick leaveUpskilling, reskilling and certification coursesUnlimited access to the LinkedIn Learning library and 22,000+ coursesGlobal career opportunitiesVolunteer and community involvement opportunitiesEPAM Employee GroupsAward-winning culture recognized by Glassdoor, Newsweek and LinkedInEPAM is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, sexual orientation, gender identity or expression, disability, protected veteran status, or any other characteristic protected by applicable law.