Senior AI Engineer: End-to-End ML & MLOps

EPAM Systems; México; On-site; MXN 900,000 - 1,200,000; Full time

Benefits offered by this job

Healthcare benefits

Paid time off

Up skilling and certification programs

LinkedIn Learning access

Global career opportunities

Volunteer opportunities

Employee Groups

Job summary

EPAM Systems is seeking a Senior AI Engineer to own the end-to-end lifecycle of ML systems, from problem framing to production deployment, delivering scalable AI-driven solutions across multi-national teams.

The role involves designing ML architectures for batch and real-time pipelines, handling large-scale data, and collaborating with product and business teams to define KPIs and success metrics. A strong ML/engineering background and English proficiency are required.

Qualifications

• 3+ years of experience in machine learning engineering or a related field.
• Expertise in MLOps practices for managing the ML lifecycle.
• Proficiency in PySpark and Python for building scalable data and ML pipelines.
• Background in designing and deploying production-grade ML systems.
• Understanding of batch and real-time data processing architectures.
• Experience working with large-scale structured and unstructured datasets.
• 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 Engineering

MLOps

PySpark

Python

Production ML

Batch/Real-time

Data Processing

English B2

Tools

Kafka

MLflow

PyTorch

Job description

EPAM Systems is seeking a Senior AI Engineer to own the end-to-end lifecycle of ML systems, from problem framing to production deployment, delivering scalable AI-driven solutions across multi-national teams.

The role involves designing ML architectures for batch and real-time pipelines, handling large-scale data, and collaborating with product and business teams to define KPIs and success metrics. A strong ML/engineering background and English proficiency are required.