Senior MLOps Engineer

EPAM Systems; México; Remoto; MXN 900.000 - 1.300.000; Tempo pieno

Vantaggi offerti da questo lavoro

Healthcare benefits

Paid time off

Professional development

Descrizione del lavoro

EPAM Systems seeks a Senior MLOps Engineer to lead the cloud transformation and end-to-end ML production lifecycle for a major real estate analytics platform. You will mentor engineers, set technical standards, and collaborate with Data Science, Engineering, and Product teams to align ML initiatives with business goals.

The role emphasizes scalable, secure data pipelines, model deployment at scale, and continuous improvement of ML observability. Strong Python and Google Cloud skills required.

Competenze

• 3+ years of experience in an MLOps or similar role.
• Advanced proficiency in Python with strong software engineering practices.
• Deep expertise in Google Vertex AI and Vertex AI Pipelines, including production-scale implementations.
• Proven experience designing and implementing monitoring, alerting, and observability for ML models in production.
• Strong hands-on experience with Jenkins and Docker in enterprise CI/CD environments.

Mansioni

• Define and govern the ML systems lifecycle across multiple teams and projects.
• Translate complex business objectives into well-framed ML problems and technical roadmaps.
• Architect scalable, secure, and cost-efficient data solutions for diverse use cases.
• Oversee data preparation and processing strategies ensuring quality, lineage and reproducibility.
• Lead model training and experimentation initiatives with standards for the team.
• Design, build, and automate robust ML pipelines and CI/CD workflows.
• Deploy models to production with focus on scalability, security, and performance.
• Monitor, optimize, and maintain models in production with advanced observability and remediation.

Conoscenze

Python

MLOps

Vertex AI

CI/CD

Jenkins

Docker

Kubernetes

Observability

Groovy

PyCharm

Strumenti

Google Vertex AI

Vertex AI Pipelines

Jenkins

Docker

Kubeflow

Kubernetes

Ansible

Terraform

JetBrains PyCharm

Groovy

Descrizione del lavoro

We are seeking a Senior 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 lead the transformation of systems to the cloud, driving cost optimization, improved availability and reliability through architectural improvements, and enhanced analytics with better TTM. You will own and evolve the end-to-end process of taking machine learning models to production, as well as establishing best practices for maintaining, monitoring, and continuously improving them. You will also mentor junior engineers, define technical standards, and collaborate with cross-functional stakeholders to shape the ML platform strategy.ResponsibilitiesDefine and govern the ML systems lifecycle across multiple teams and projectsTranslate complex business objectives into well-framed ML problems and technical roadmapsArchitect scalable, secure, and cost-efficient data solutions tailored to diverse use casesOversee data preparation and processing strategies, ensuring quality, lineage, and reproducibilityLead model training and experimentation initiatives, establishing frameworks and standards for the teamDesign, build, and automate robust, reusable ML pipelines and CI/CD workflowsDeploy models to production systems with a focus on scalability, security, and performanceMonitor, optimize, and maintain models in production, implementing advanced observability, drift detection, and automated remediationMentor and provide technical leadership to junior and middle engineersCollaborate with Data Science, Engineering, and Product teams to align ML initiatives with business goalsDrive architectural decisions and contribute to the long-term MLOps strategyRequirements3+ years of experience in an MLOps or similar roleAdvanced proficiency in Python, with strong software engineering practicesDeep expertise in Google Vertex AI and Google Vertex AI Pipelines, including production-scale implementationsProven experience designing and implementing monitoring, alerting, and observability for ML models in productionStrong hands-on experience with Jenkins and Docker in enterprise CI/CD environmentsExperience architecting end-to-end ML platforms and establishing MLOps best practicesEnglish proficiency at B2 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.