
Description
Description
SAIC is seeking an experienced AI/ML Engineer to help build and maintain the Analytics Application Platform (AAP), a full-fledged platform that provides both laboratory and factory services. AAP is designed as the IRS's primary AI/ML Platform-as-a-Service (PaaS), securely delivering mission-driven data science solutions at scale. This platform supports a wide range of use cases, from traditional model development to integrating Generative AI (GenAI) capabilities. As an AI/ML Engineer, you will play a crucial role in maturing the platform, ensuring it is production-ready, scalable, and compliant with IRS requirements, and you will support the platform regardless of the specific technologies or services being used, including Databricks and AWS SageMaker/Bedrock.
Key Responsibilities:
- Develop and maintain robust data exploration and feature engineering pipelines to ensure data readiness for modeling within a secure and compliant infrastructure.
- Implement and manage modern AI/ML tools such as Databricks, JupyterHub, AWS SageMaker, and Bedrock, for exploratory data analysis, AI design, model development, and training.
- Integrate platform tools with TCloud Bitbucket for efficient version control, collaboration, and continuous integration/continuous deployment (CI/CD) processes.
- Configure AWS S3 buckets for a Feature Store, ensuring compliance with IRS UNAX rules and maintaining distinct security contexts for different teams.
- Establish and maintain a comprehensive model development pipeline utilizing MLflow for experiment tracking, model registry, and lifecycle management.
- Create AWS Lambda functions and implement AWS Flow for efficient model artifact storage and metadata management.
- Integrate with AWS RDS for robust data management and retrieval capabilities.
- Configure SNS notifications to facilitate model promotion workflows.
- Support teams in adhering to Responsible AI Principles by implementing the Responsible AI Toolbox, ensuring ethical and compliant AI/ML practices.
- Leverage both Databricks and AWS services such as SageMaker and Bedrock to build and deploy large language models (LLMs), enabling IRS customers to create and integrate advanced Generative AI applications.
- Ensure that all AI/ML development and deployment activities adhere to strict security and privacy standards, especially in compliance with IRS regulations.
- Contribute to the iterative maturation of the platform, ensuring new capabilities are production-ready and scalable.
- Develop support models, documentation, and processes that simplify the customer experience and enable their success in navigating the platform.
- Work collaboratively to instill confidence in the platform, ensuring it goes beyond technical completeness to truly enable and scale AI/ML solutions.
Qualifications
Required:
- Bachelor's or master's degree in Computer Science, Engineering, or a related field. A PhD is preferred.( 4 years experience in lieu of degree)
- At least 9 years of experience in AI/ML, cloud services, and platform management, particularly with both Databricks and AWS (including S3, Lambda, RDS, SNS, SageMaker, and Bedrock).
- Proven expertise in setting up and managing environments with tools such as Databricks, JupyterHub, MLflow, and Bitbucket.
- Strong proficiency in programming languages and tools such as SQL, Python, R, and Spark. Familiarity with machine learning frameworks and libraries, including those used for building and deploying LLMs.
- Deep understanding of data security and privacy, especially in compliance with IRS standards.
- Experience with CI/CD pipelines and infrastructure as code.
- Excellent communication skills with the ability to collaborate effectively with cross-functional teams and articulate complex technical concepts to stakeholders.
Desired:
- Previous experience working in a regulated environment, particularly within government agencies like the IRS.
- Relevant certifications related to AWS or cloud architecture.
- Knowledge of Responsible AI practices and principles.
Target salary range: $160,001 - $200,000. The estimate displayed represents the typical salary range for this position based on experience and other factors.
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