Lead AI Engineer

EPAM Systems; Argentina; Remote; ARS 1,500,000 - 2,500,000; Full time

Benefits offered by this job

Healthcare benefits

Paid time off

Professional development

Global career opportunities

Job summary

EPAM Systems in Argentina seeks a Lead AI Engineer to drive ML systems from concept to production. You will design scalable architectures, build robust pipelines, and partner with cross-functional teams to deliver AI solutions.

The role requires 5+ years in ML engineering, 1+ year leadership, and strong MLOps expertise. Proficiency in PySpark, Python, Kafka, MLflow, and PyTorch is advantageous. Hybrid or on-site options may apply, with global projects and ongoing learning opportunities.

Qualifications

• Over 5 years of experience in machine learning engineering or related field.
• At least 1 year of leadership experience.
• Strong expertise in MLOps practices for overseeing the ML lifecycle.
• Proven background in designing and launching production-grade ML systems.

Responsibilities

• Lead the complete ML lifecycle from problem formulation to monitoring.
• Design scalable ML architectures and robust data pipelines (batch and real-time).
• Collaborate with cross-functional teams to establish KPIs and success metrics.
• Ensure production readiness with optimized latency, scalability, and cost.

Skills

Leadership experience

English proficiency (B2+)

Problem solving

Tools

PySpark

Python

Apache Kafka

MLflow

PyTorch

Job description

We are seeking a Lead AI Engineer to manage machine learning systems from initial concept through to production launch. This role involves designing scalable ML architectures, building robust pipelines, and working with cross-functional teams to deliver effective AI solutions.ResponsibilitiesManage the complete ML systems lifecycle, covering problem formulation, data collection, feature engineering, model training, evaluation, deployment, and monitoringCreate and implement scalable ML architectures, including both batch and real-time pipelinesHandle large-scale structured and unstructured datasets, such as clickstream, transactional, text, and image dataBuild and launch models like recommendation systems, ranking models, forecasting models, and classification/regression systemsUtilize deep learning methods, including neural networks, transformers, and representation learning, as neededEstablish and maintain feature stores, model registries, and experiment tracking systemsGuarantee production readiness by optimizing for latency, scalability, reliability, and cost efficiencyPartner with engineering, product, and business teams to establish KPIs and success metricsRequirementsOver 5 years of experience in machine learning engineering or a related disciplineAt least 1 year of applicable leadership experienceStrong expertise in MLOps practices for overseeing the ML lifecycleSkilled in PySpark and Python for developing scalable data and ML pipelinesProven background in designing and launching production-grade ML systemsSolid understanding of batch and real-time data processing architecturesExperience handling large-scale structured and unstructured datasetsEnglish language skills at a B2 level or aboveNice to haveExperience with Apache Kafka and MLflowKnowledge of machine learning concepts 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 LinkedIn