Data Science Engineering Manager (AWS SageMaker & Bedrock)
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
- Upper-Intermediate English proficiency (B2, Upper-Intermediate)
Nice to have
- Experience with Amazon Lookout for anomaly detection on industrial or operational data
