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EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our customers, our employees, and our communities. We embrace a dynamic and inclusive culture. Here you will collaborate with multi-national teams, contribute to a myriad of innovative projects that deliver the most creative and cutting-edge solutions, and have an opportunity to continuously learn and grow. No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential.

We are building cloud-ready AI/ML solutions on AWS for optimization and forecasting in the energy (oil & gas) sector across parallel workstreams. As the Data Science Engineering Manager (AWS SageMaker & Bedrock), you will blend hands-on ML engineering with stakeholder leadership to deliver production‑grade outcomes on Amazon SageMaker and Amazon Bedrock—apply now to help clients achieve measurable value from AI.

Responsibilities

- Lead the design, development, and deployment of optimization and forecasting models on Amazon SageMaker
- Build end‑to‑end ML workflows covering data preparation, feature engineering, training, evaluation, and inference
- Architect scalable, cost‑efficient, production‑ready inference solutions aligned to AWS best practices
- Apply Amazon Bedrock to deliver generative AI solutions for document processing, knowledge extraction, and automation
- Drive technical decisions across workstreams and provide escalation support for AI/ML topics
- Coordinate delivery across multiple parallel engagements while managing priorities and timelines
- Collaborate with client data teams, domain experts, and AWS Professional Services to align solutions to business goals




- Implement monitoring, logging, and model governance using AWS‑native tooling
- Apply AWS Well‑Architected Framework principles with focus on security, reliability, performance, and cost optimization
- Document model architectures, pipeline configurations, and operational procedures for maintainability
- Deliver knowledge transfer sessions and produce handover materials to enable client self‑sufficiency

Requirements

- 8+ years of experience in data science and machine learning solutions development
- Hands‑on experience with Amazon SageMaker for training, hosting, and pipelines
- Solid background in building optimization and forecasting models
- Proven leadership experience managing multiple parallel client engagements
- Strong stakeholder management skills with executive‑level communication
- Deep understanding of AWS cloud‑native best practices for production AI/ML solutions
- Hands‑on MLOps skills across data preparation, feature engineering, evaluation, and inference
- Advanced energy domain experience in oil & gas or industrial AI/ML use cases
- Strong problem‑solving skills with ability to operate independently across workstreams

Nice to have

- Experience with Amazon Lookout for anomaly detection on industrial or operational data

We offer

- International projects with top brands
- Work with global teams of highly skilled, diverse peers
- Employee financial programs
- Paid time off and sick leave
- Upskilling, reskilling and certification courses
- Unlimited access to the LinkedIn Learning library and 22,000+ courses
- Integral career opportunities
- Volunteer and community involvement opportunities
- EPAM Employee Groups
- Award‑winning culture recognized by Glassdoor, Newsweek and LinkedIn

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Postúlate en Kit Empleo: kitempleo.com.co/empleo/1aauqk

📌 Data Science Engineering Manager (AWS SageMaker & Bedrock) (Colombia)
🏢 EPAM Systems
📍 Colombia