Senior AI Engineer — End-to-End ML & Real-Time Pipelines

EPAM Systems; Argentina; Presencial; ARS 1 200 000 - 1 800 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Healthcare benefits

Global teams

Paid time off

Upskilling & certification courses

LinkedIn Learning access

Volunteer opportunities

Resumo da oferta

EPAM Systems seeks a Senior AI Engineer to own the end-to-end lifecycle of ML systems, from problem formulation to deployment and monitoring. You will design scalable architectures and production-grade models across diverse use cases while collaborating with cross-functional teams.

The role emphasizes building pipelines, feature stores, and experiment tracking, with a strong focus on latency, reliability, and cost efficiency in production environments.

Qualificações

• 3+ years of experience building and deploying ML systems in production environments.
• Expertise in 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 (neural networks, transformers, representation learning).
• Experience building feature stores, model registries, and experiment tracking systems.
• Understanding of production readiness: latency, scalability, reliability, cost efficiency.
• Ability to collaborate with engineering, product, and business to define KPIs and metrics.
• English proficiency at B2 level or higher.

Responsabilidades

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

Conhecimentos

ML system design

Real-time data pipelines

Large-scale data processing

Deep learning techniques

Cross-functional collaboration

Ferramentas

Feature stores

Model registries

Experiment tracking

Descrição da oferta de emprego

EPAM Systems seeks a Senior AI Engineer to own the end-to-end lifecycle of ML systems, from problem formulation to deployment and monitoring. You will design scalable architectures and production-grade models across diverse use cases while collaborating with cross-functional teams.

The role emphasizes building pipelines, feature stores, and experiment tracking, with a strong focus on latency, reliability, and cost efficiency in production environments.