Machine Learning Engineer (Washington) Job at Booz Allen Hamilton, Washington DC

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  • Booz Allen Hamilton
  • Washington DC

Job Description

Machine Learning Engineer

Do you enjoy creating innovative solutions to complex challenges while working within a community of dynamic technology professionals? As an experienced data professional, you know that machine learning is critical to understanding and processing massive datasets. We need your technical expertise to support federal healthcare.

As a machine learning engineer, you will break down use cases, design, and implement complex system modules, interfaces, and features. You will leverage your expertise in AI, develop new robust, secure, and performant productiongrade software, and work with a team to build, test, and operate system capabilities. You will apply your knowledge of fullstack web application development, software design, and implementation on large codebases, and quickly learn new languages, technologies, and codebases. You will work independently while collaborating with a team to build complex features, integrations, and modules, and guide clients as they navigate the landscape of ML algorithms, tools, and frameworks.

Join us. The world cant wait.

Qualifications

  • 2+ years of experience with machine learning engineering in an academic or professional environment
  • Experience with natural language processing and language models
  • Experience with Retrieval-Augmented Generation (RAG) and generative AI techniques
  • Programming experience in Python, Java, or C++
  • TS/SCI clearance
  • Bachelor's degree

Nice to Have

  • Experience with developing software architectures using containerization tools such as Docker and Kubernetes
  • Experience with machine learning methods including linear, reinforcement, treebased, or deeplearning approaches and regularization techniques
  • Experience with databases, including SQL
  • Experience with software development, API development or database management, and model deployment and usage with JavaScript frameworks such as React, Angular, or Node.js
  • Knowledge of AWS, Azure, and GCP
  • Ability to work in a Linux environment with Bash scripting
  • Master's degree

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, skills, and experience. The projected compensation range for this position is $77,600.00 to $176,000.00 (annualized USD). This estimate represents the typical salary range for this position and is one component of Booz Allen's total compensation package. This posting will close within 90 days from the posting date.

At Booz Allen, we celebrate your contributions, provide opportunities and choices, and support your total wellbeing. Our offerings include health, life, disability, financial, and retirement benefits, paid leave, professional development, tuition assistance, worklife programs, and dependent care. The recognition awards program acknowledges employees for exceptional performance and alignment with our values. Fulltime and parttime employees working at least 20 hours a week are eligible to participate in Booz Allens benefit programs.

Identity Statement

As part of the application process, you are expected to be on camera during interviews and assessments. We reserve the right to take your picture to verify your identity and prevent fraud.

Work Model

  • If this position is listed as remote or hybrid, youll periodically work from a Booz Allen or client site facility.
  • If this position is listed as onsite, youll work with colleagues and clients in person, as needed for the specific role.

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.

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Job Tags

Full time, Part time, Local area, Remote work,

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