Senior AI Engineer

EPAM Systems; Brasil; Remote; BRL 350,000 - 550,000; Full time

Job summary

EPAM Systems in Brazil seeks a Senior AI Engineer to own the end-to-end lifecycle of ML systems, from problem formulation to production deployment. You will design scalable architectures and robust data pipelines.

You will work with large-scale datasets, implement models such as recommender, forecasting, and classification systems, and collaborate with cross-functional teams to define KPIs and ensure production readiness.

Qualifications

• 3+ years of experience in machine learning engineering or related field.
• Experience with MLOps practices for managing the ML lifecycle.
• Proficiency in Python and PySpark for building scalable pipelines.

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 datasets such as clickstream, transactional, text, and image data.
• Develop and deploy models such as recommendation systems, forecasting, and classification/regression.
• 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

Python

PySpark

MLOps

Transformers

PyTorch

Tools

Apache Kafka

MLflow

Feature stores

Model registries

Job description

We are looking for a Senior AI Engineer to own the end-to-end lifecycle of machine learning systems, from problem formulation to production deployment. You will design scalable ML architectures, build robust pipelines, and collaborate across teams to deliver impactful AI-driven solutions.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 machine learning engineering or a related fieldExpertise in MLOps practices for managing the ML lifecycleProficiency in PySpark and Python for building scalable data and ML pipelinesBackground in designing and deploying production-grade ML systemsUnderstanding of batch and real-time data processing architecturesExperience working with large-scale structured and unstructured datasetsEnglish proficiency at B2 level or higherNice to haveFamiliarity with Apache Kafka and MLflowKnowledge of Machine Learning and PyTorchWe 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.