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Selected role

MLOps Engineer - AWS, Development

Jobs via Dice Washington, DC

Senior Full-time

Dice is the leading career destination for tech experts at every stage of their careers. Our client, SES, is seeking the following. Apply via Dice today!

MLOps Engineer - AWS, Development
Type: W2 With Benefits - No C2C
Location: Washington DC - 2 or 3 days per week onsite
Top 5 Technical Skills:

MLOps
Python
AWS (SageMaker, S3, EC2, EKS/Fargate, Lambda, AWS Glue, and IAM)
Docker/Terraform
CICD

Job Description:
We are seeking an experienced and highly skilled AWS Full Stack ML Engineer to operationalize and optimize our large-scale financial modeling applications. This role requires a unique blend of expertise in machine learning, software engineering, and AWS cloud infrastructure, with a strong focus on implementing robust MLOps practices to ensure scalability, reliability, and cost-efficiency. The ideal candidate will bridge the gap between data science and production systems, transforming data science prototypes into secure, high-performance, and compliant solutions in a fast-paced financial environment.?
Key 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.
System Design and Integration: Reengineer large scale model development code (from data scientists) and model application code (from software engineers) and seamlessly integrate 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.
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).
Optimize AWS Service Usage:?Monitor and optimize AWS resource utilization to ensure cost-effectiveness, high availability, and performance for compute-intensive financial modeling applications.
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.?
Required Skills and Qualifications
Experience: Proven experience (6+ years preferred) in MLOps, DevOps, or a related role, with hands-on experience in developing and deploying ML applications at scale.
Programming Proficiency: Strong proficiency in Python and relevant ML libraries/frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
AWS Expertise: In-depth experience with key AWS services for ML and data, including Amazon SageMaker, S3, EC2, EKS/Fargate, Lambda, AWS Glue, and IAM.
MLOps Tools: Experience with containerization (Docker), orchestration (ECS//EKS), CI/CD tools (GitLab, AWS CodePipeline, Jenkins), and workflow orchestrators (AWS Step Functions, Apache Airflow).
Financial Domain Knowledge (Preferred): Familiarity with the specific challenges and regulatory environment surrounding financial modeling and data is a strong plus.
Software Engineering Best Practices: Solid understanding of software system design, microservice implementation, development lifecycle, including testing, debugging, version control (Git), and quality standards code.
Problem-Solving: Excellent analytical and problem-solving skills, with the ability to troubleshoot complex, interconnected systems.
Education: A Bachelor's or Master's degree in Computer Science, Engineering, Statistics, or a related quantitative field
Certifications (Preferred): AWS Certified Machine Learning - Specialty certification, AWS Certified Solutions Architect Associate, or other relevant cloud certifications.

Benefits:
SES hires W2 benefitted and non-benefitted consultants. Our contract employee benefits include group medical dental vision life LT and ST disability insurance, 21 days of accrued paid time off, 401k, tuition reimbursement, performance bonuses, paid overtime, and more.
Please contact me to discuss the details of this position further.

Please forward resume directly to for immediate consideration - rstarinieri at sesc .com

*I look forward to speaking with you soon!
Robin Starinieri
Director of Recruiting
Systems Engineering Services

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