Booz Allen Hamilton
Overview
Join to apply for the
MLOps Engineer, Senior
role at Booz Allen Hamilton Job Number: R0223861 The Opportunity : Are you looking for an opportunity to make a difference and help build a system that will have a positive impact in the intelligence community (IC)? What if you could find a position that is tailor made for your mix of development, engineering, and analytics? Efficient development teams make the most of their time by limiting the activities that take developers and data scientists away from writing their code. That’s why we need you, an experienced machine learning engineer, to help us design and architect an MLOps platform in the Cloud that shortens the time it takes to get new capabilities from development to production, to support mission critical operations. As an MLOps Engineer on our team, you’ll use your development experience to streamline our development life cycle from development to production. You’ll be working with a collaborative Agile development team to build and maintain Cloud software and infrastructure that supports machine learning across the enterprise. You’ll implement continuous integration and deployment to development, testing, and production environments. This is an opportunity to broaden your skill set into areas like Agile development, Cloud-based development, containerization, and serverless while developing software that will improve national security. As a machine learning engineer, you’ll identify new opportunities to build solutions and architecture to help your customers meet their toughest challenges. Join our team as we build tools to transform the future of the IC. Join us. The world can’t wait. Responsibilities
Use development experience to streamline the development life cycle from development to production Collaborate with an Agile development team to build and maintain Cloud software and infrastructure that supports machine learning across the enterprise Implement continuous integration and deployment to development, testing, and production environments Develop skills in Agile development, Cloud-based development, containerization, and serverless architectures Design and architect an MLOps platform in the Cloud to shorten time from development to production for mission critical operations Qualifications
4+ years of experience with Object-Oriented Programming (OOP), including in Python 4+ years of experience with developing containerized applications, including API design and authentication 3+ years of experience with developing software using cloud technologies, including AWS 3+ years of experience with leveraging MLOps platforms and ML CI/CD workflows to manage datasets and model training, deployment, and monitoring Knowledge of the ML lifecycle and concepts to develop an MLOps ecosystem TS/SCI clearance HS diploma or GED Ability to obtain a Security+ CE, SSCP, CCNA-Security, or GSEC certification within 6 months of hire Nice If You Have
Experience developing prompts, tools, and agents with LLMs Experience with AWS SageMaker, Lambda, API Gateway, DynamoDB, S3, and IAM Experience with Kubernetes Experience with IaC tools like Helm and Terraform Experience with design and implementation, including building, containerizing, and deploying end-to-end automated data and ML pipelines, within a Cloud environment Experience with version control tools, including Git Bachelor’s degree preferred; Master’s degree a plus Security+ CE, SSCP, CCNA-Security, or GSEC Certification Clearance
Applicants selected will be subject to a security investigation and may need to meet eligibility requirements for access to classified information; TS/SCI clearance is required. Compensation
Salary at Booz Allen is determined by various factors, including location, education, knowledge, skills, competencies, experience, contract-specific affordability, and organizational requirements. The projected compensation range for this position is $99,000.00 to $225,000.00 (annualized USD). The posting will close within 90 days from the Posting Date. Work Model
Our people-first culture prioritizes the benefits of flexibility and collaboration, whether that happens in person or remotely. Commitment to Non-Discrimination
All qualified applicants will receive consideration for employment without regard to disability, status as a protected veteran or any other status protected by applicable federal, state, local, or international law.
#J-18808-Ljbffr
Join to apply for the
MLOps Engineer, Senior
role at Booz Allen Hamilton Job Number: R0223861 The Opportunity : Are you looking for an opportunity to make a difference and help build a system that will have a positive impact in the intelligence community (IC)? What if you could find a position that is tailor made for your mix of development, engineering, and analytics? Efficient development teams make the most of their time by limiting the activities that take developers and data scientists away from writing their code. That’s why we need you, an experienced machine learning engineer, to help us design and architect an MLOps platform in the Cloud that shortens the time it takes to get new capabilities from development to production, to support mission critical operations. As an MLOps Engineer on our team, you’ll use your development experience to streamline our development life cycle from development to production. You’ll be working with a collaborative Agile development team to build and maintain Cloud software and infrastructure that supports machine learning across the enterprise. You’ll implement continuous integration and deployment to development, testing, and production environments. This is an opportunity to broaden your skill set into areas like Agile development, Cloud-based development, containerization, and serverless while developing software that will improve national security. As a machine learning engineer, you’ll identify new opportunities to build solutions and architecture to help your customers meet their toughest challenges. Join our team as we build tools to transform the future of the IC. Join us. The world can’t wait. Responsibilities
Use development experience to streamline the development life cycle from development to production Collaborate with an Agile development team to build and maintain Cloud software and infrastructure that supports machine learning across the enterprise Implement continuous integration and deployment to development, testing, and production environments Develop skills in Agile development, Cloud-based development, containerization, and serverless architectures Design and architect an MLOps platform in the Cloud to shorten time from development to production for mission critical operations Qualifications
4+ years of experience with Object-Oriented Programming (OOP), including in Python 4+ years of experience with developing containerized applications, including API design and authentication 3+ years of experience with developing software using cloud technologies, including AWS 3+ years of experience with leveraging MLOps platforms and ML CI/CD workflows to manage datasets and model training, deployment, and monitoring Knowledge of the ML lifecycle and concepts to develop an MLOps ecosystem TS/SCI clearance HS diploma or GED Ability to obtain a Security+ CE, SSCP, CCNA-Security, or GSEC certification within 6 months of hire Nice If You Have
Experience developing prompts, tools, and agents with LLMs Experience with AWS SageMaker, Lambda, API Gateway, DynamoDB, S3, and IAM Experience with Kubernetes Experience with IaC tools like Helm and Terraform Experience with design and implementation, including building, containerizing, and deploying end-to-end automated data and ML pipelines, within a Cloud environment Experience with version control tools, including Git Bachelor’s degree preferred; Master’s degree a plus Security+ CE, SSCP, CCNA-Security, or GSEC Certification Clearance
Applicants selected will be subject to a security investigation and may need to meet eligibility requirements for access to classified information; TS/SCI clearance is required. Compensation
Salary at Booz Allen is determined by various factors, including location, education, knowledge, skills, competencies, experience, contract-specific affordability, and organizational requirements. The projected compensation range for this position is $99,000.00 to $225,000.00 (annualized USD). The posting will close within 90 days from the Posting Date. Work Model
Our people-first culture prioritizes the benefits of flexibility and collaboration, whether that happens in person or remotely. Commitment to Non-Discrimination
All qualified applicants will receive consideration for employment without regard to disability, status as a protected veteran or any other status protected by applicable federal, state, local, or international law.
#J-18808-Ljbffr