Chief Data Science Engineer (AWS SageMaker & Bedrock)
We are building cloud-native AI/ML products on AWS that deliver optimization and forecasting value for energy (oil & gas) clients at scale. As the Chief Data Science Engineer (AWS SageMaker & Bedrock), you will lead multiple parallel engagements while staying hands-on with SageMaker, Bedrock, and production MLOps. Bring your leadership and delivery mindset and apply today.
Responsibilities
- Lead the design, build, and rollout of optimization and forecasting models on Amazon SageMaker
- Develop end-to-end ML workflows covering data preparation, feature engineering, training, evaluation, and inference
- Architect scalable, cost-efficient, production-grade inference solutions aligned with AWS best practices
- Use Amazon Bedrock to deliver generative AI for document processing, knowledge extraction, and automation
- Drive technical choices across workstreams and provide escalation support for AI/ML topics
- Coordinate delivery across multiple parallel engagements and manage 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 focused on security, reliability, performance, and cost optimization
- Document model architectures, pipeline configurations, and operational procedures for maintainability
- Deliver knowledge transfer sessions and create handover materials to enable client self-sufficiency
Requirements
- 7+ 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 running 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
- Demonstrated MLOps skills spanning data preparation, feature engineering, evaluation, and inference
- Advanced energy domain experience in oil & gas or industrial AI/ML use cases
- Excellent problem-solving ability with confidence operating 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
