Senior AI Engineer

EPAM Systems; Colombia; Remote; COP 120,000,000 - 210,000,000; Full time

Job summary

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

You will design scalable architectures, work with large-scale datasets (clickstream, transactional, text, image), and develop models such as recommendations, ranking, forecasting, and classification, while ensuring production readiness and cost efficiency.

Qualifications

• 3+ years of experience building and deploying ML systems in production.
• Experience designing scalable ML architectures with batch and real-time pipelines.
• Experience with large-scale structured and unstructured data (clickstream, transactional, text, and image).
• Experience developing recommendation systems, ranking models, forecasting models, and classification/regression models.
• Knowledge of deep learning techniques including neural networks, transformers, and representation learning.
• Experience building feature stores, model registries, and experiment tracking.
• Understanding latency, scalability, reliability, and cost efficiency in production environments.
• Ability to collaborate with engineering, product, and business teams to define KPIs and success metrics.
• English proficiency at B2 level or higher.

Responsibilities

• Own end-to-end lifecycle of ML systems: problem formulation, data collection, feature engineering, model training, evaluation, deployment, and monitoring.
• Design and implement scalable ML architectures including batch and real-time pipelines.
• Work with large-scale structured and unstructured datasets such as clickstream, transactional, text, and image data.
• Develop and deploy models such as recommendation systems, ranking models, forecasting models, and classification/regression systems.
• Apply deep learning techniques including neural networks, transformers, and representation learning where appropriate.
• Build and maintain feature stores, model registries, and experiment tracking systems.
• Ensure production readiness through latency optimization, scalability, reliability, and cost efficiency.
• Collaborate with engineering, product, and business teams to define KPIs and success metrics.

Skills

ML architecture design

Real-time pipelines

Batch pipelines

Data processing

Cross-functional collaboration

KPI definition

Tools

Feature stores

Model registries

Experiment tracking

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.