Senior Machine Learning Engineer - AWS/Generative AI

Job Overview :

We are seeking a highly skilled and independent Senior Machine Learning Engineer Contractor to design, develop, and deploy advanced ML pipelines in an AWS environment. In this role, you will build cutting-edge solutions that automate entity matching for master data management, implement fraud detection systems, handle transaction matching, and integrate GenAI capabilities. The ideal candidate will have extensive hands-on experience in AWS services such as SageMaker, Bedrock, Lambda, Step Functions, and S3, as well as strong expertise in CI/CD practices to ensure a robust and scalable solution.

Key Responsibilities :

ML Pipeline Design & Development :

- Architect, develop, and maintain end-to-end ML pipelines focused on entity matching, fraud detection, and transaction matching.

- Integrate generative AI (GenAI) solutions using AWS Bedrock to enhance data processing and decision-making.

- Collaborate with cross-functional teams to refine business requirements and develop data-driven solutions tailored to master data management needs.

AWS Ecosystem Expertise :

- Utilize AWS SageMaker for model training, deployment, and continuous improvement.

- Leverage AWS Lambda and Step Functions to orchestrate serverless workflows for data ingestion, preprocessing, and real-time processing.

- Manage data storage, retrieval, and scalability concerns using AWS S3.

CI/CD Implementation :

- Develop and integrate automated CI/CD pipelines (using tools such as GitLab) to streamline model testing, deployment, and version control.

- Ensure rapid iteration and robust deployment practices to maintain high availability and performance of ML solutions.

Data Security & Compliance :

- Implement security best practices to safeguard sensitive data, ensuring compliance with organizational and regulatory requirements.

- Incorporate monitoring and alerting mechanisms to maintain the integrity and performance of deployed ML models.

Collaboration & Documentation :

- Work closely with business stakeholders, data engineers, and data scientists to ensure solutions align with evolving business needs.

- Document all technical designs, workflows, and deployment processes to support ongoing maintenance and future enhancements.

- Provide regular progress updates and adapt to changing priorities or business requirements in a dynamic environment.

Required Qualifications :

Technical Expertise :

- 5+ years of professional experience in developing and deploying ML models and pipelines.

- Proven expertise in AWS services including SageMaker, Bedrock, Lambda, Step Functions, and S3.

- Strong proficiency in Python and/or PySpark for data manipulation, model development, and pipeline implementation.

- Demonstrated experience with CI/CD tools and methodologies, preferably with GitLab or similar version control systems.

- Practical experience in building solutions for entity matching, fraud detection, and transaction matching within a master data management context.

- Familiarity with generative AI models and their application within data processing workflows.

Analytical & Problem-Solving Skills :

- Ability to transform complex business requirements into scalable technical solutions.

- Strong data analysis capabilities with a track record of developing models that provide actionable insights.

Communication & Collaboration :

- Excellent verbal and written communication skills.

- Demonstrated ability to work independently as a contractor while effectively collaborating with remote teams.

- Proven record of quickly adapting to new technologies and agile work environments.

Preferred Qualifications :

- Bachelors or Masters degree in Computer Science, Data Science, Engineering, or a related field.

- Experience with additional AWS services such as Kinesis, Firehose, and SQS.

- Prior experience in a consulting or contracting role, demonstrating the ability to manage deliverables under tight deadlines.

- Experience within industries where data security and compliance are critical.

- To adhere to the Information Security Management policies and procedures