ThoughtStorm · 7 hours ago
AWS Full Stack ML Engineer
Reston, VA
Contract
Onsite
Mid, Senior Level
4+ years expThoughtStorm is seeking an experienced and highly skilled AWS Full Stack ML Engineer to operationalize and optimize large-scale financial modeling applications. This role involves implementing MLOps practices and bridging the gap between data science and production systems to create secure, high-performance solutions in a fast-paced financial environment.
Cloud ComputingConsultingInformation TechnologyProfessional ServicesCloud Infrastructure
Responsibilities
Implement MLOps and CI/CD: Design, build, and maintain end-to-end MLOps pipelines for the continuous integration, training, deployment, and monitoring of ML models on AWS
Code Integration: Seamlessly integrate model development code (from data scientists) and model application code (from software engineers) into unified, production-ready systems
Automate Data Processing: Design and manage scalable and efficient ETL pipelines and data processing workflows for large-scale financial datasets, ensuring data quality and availability for model training and inference
Optimize AWS Service Usage: Monitor and optimize AWS resource utilization to ensure cost-effectiveness, high availability, and performance for compute-intensive financial modeling applications
Infrastructure Management: Utilize Infrastructure as Code (IaC) tools like Terraform or AWS CloudFormation to provision and manage secure, compliant, and reproducible ML infrastructure
Monitoring and Alerting: Implement robust monitoring, logging, and alerting frameworks (e.g., Amazon CloudWatch) to track model performance, data drift, and system health in production
Security and Compliance: Ensure all ML systems adhere to stringent financial industry regulations and security best practices (e.g., data encryption, IAM roles, VPC configurations)
Collaboration: Work closely with cross-functional teams, including data scientists, data engineers, and software developers, to translate business requirements into technical solutions and champion MLOps best practices across the organization
Qualification
Required
Proven experience (4+ years preferred) in MLOps, DevOps, or a related role, with hands-on experience deploying ML applications at scale
Strong proficiency in Python and relevant ML libraries/frameworks (e.g., TensorFlow, PyTorch, Scikit-learn)
In-depth experience with key AWS services for ML and data, including Amazon SageMaker, S3, EC2, EKS/Fargate, Lambda, AWS Glue, and IAM
Experience with containerization (Docker), orchestration (ECS/Kubernetes/EKS), CI/CD tools (GitLab, AWS CodePipeline, Jenkins), and workflow orchestrators (Apache Airflow or AWS Step Functions)
Solid understanding of software development lifecycle, including testing, debugging, version control (Git), and code quality standards
Excellent analytical and problem-solving skills, with the ability to troubleshoot complex, interconnected systems
A Bachelor's or Master's degree in Computer Science, Engineering, Statistics, or a related quantitative field
Preferred
Familiarity with the specific challenges and regulatory environment surrounding financial modeling and data is a strong plus
AWS Certified Machine Learning - Specialty certification, AWS Certified Solutions Architect – Associate, or other relevant cloud certifications
Company
ThoughtStorm
ThoughtStorm offers information technology and consulting services.
51-200 employees
Funding
Current Stage
Growth StageCompany data provided by crunchbase