Senior AI Engineer

EPAM Systems; México; Remote; MXN 900,000 - 1,300,000; Full time

Job summary

EPAM Systems, Inc. is seeking a Senior AI Engineer to own the end-to-end lifecycle of ML systems—from problem framing and data collection to model training, deployment and monitoring.

You will design scalable architectures, build batch and real-time data pipelines, and work with large-scale datasets across text, image, and clickstream data. You will develop models such as recommender, ranking, forecasting and classification systems, apply deep learning techniques, and maintain feature stores and

Qualifications

• 3+ years of experience building and deploying ML systems in production.
• Experience designing scalable ML architectures with batch and real-time pipelines.
• Proficiency with large-scale structured and unstructured datasets (clickstream, transactional, text, image).
• Experience developing recommendation, ranking, forecasting, and classification/regression models.
• Knowledge of deep learning techniques including neural nets, transformers, and representation learning.
• Experience building feature stores, model registries, and experiment tracking.
• Understanding production readiness: latency, scalability, reliability, cost efficiency.
• Ability to collaborate with engineering, product, and business teams to define KPIs.

Responsibilities

• Own end-to-end lifecycle of ML systems from problem framing to monitoring.
• Design and implement scalable ML architectures and data pipelines.
• Collaborate with cross-functional teams to define KPIs and success metrics.
• Ensure production readiness with latency optimization and cost efficiency.

Job description

We are seeking a Senior AI Engineer to own the end-to-end lifecycle of ML systems, from problem formulation and data collection through model training, deployment, and monitoring. This role involves designing scalable architectures and deploying production-grade models across a variety of use cases while collaborating closely with cross-functional teams.ResponsibilitiesOwn end-to-end lifecycle of ML systems: problem formulation, data collection, feature engineering, model training, evaluation, deployment, and monitoringDesign and implement scalable ML architectures including batch and real-time pipelinesWork with large-scale structured and unstructured datasets such as clickstream, transactional, text, and image dataDevelop and deploy models such as recommendation systems, ranking models, forecasting models, and classification/regression systemsApply deep learning techniques including neural networks, transformers, and representation learning where appropriateBuild and maintain feature stores, model registries, and experiment tracking systemsEnsure production readiness through latency optimization, scalability, reliability, and cost efficiencyCollaborate with engineering, product, and business teams to define KPIs and success metricsRequirements3+ years of experience in building and deploying ML systems in production environmentsExpertise in designing scalable ML architectures, including batch and real-time pipelinesProficiency in working with large-scale structured and unstructured datasets, including clickstream, transactional, text, and image dataExperience developing recommendation systems, ranking models, forecasting models, and classification/regression systemsKnowledge of deep learning techniques including neural networks, transformers, and representation learningSkills in building and maintaining feature stores, model registries, and experiment tracking systemsUnderstanding of production readiness considerations such as latency optimization, scalability, reliability, and cost efficiencyCapability to collaborate with engineering, product, and business teams to define KPIs and success metricsEnglish proficiency at B2 level or higherWe 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.