The Opportunity:
Are you looking for an opportunity to make a difference and help build innovative systems that will have a positive impact on how scientific systems are delivered? What if you could find a position that is tailor-made for your mix of science, AI, ML, and engineering skills? Scientific AI and ML engineers play a critical role in advancing research and operational innovation through cutting-edge applications of machine learning and artificial intelligence. That’s why we need an experienced AI and ML engineer like you to help us design and develop solutions that combine domain expertise, scientific rigor, and machine learning techniques to deliver actionable insights and support mission-critical operations.
As a Scientific AI & ML Engineer on our team, you’ll apply your deep technical expertise to create innovative machine learning and AI algorithms, frameworks, and tools to address complex scientific challenges. You’ll collaborate with a multidisciplinary Agile development team to develop, validate, and optimize AI and ML models and workflows. Whether it’s designing novel algorithms, enabling automation of AI workflows, or scaling solutions in a cloud environment, you’ll have the opportunity to pioneer new approaches while improving scientific outcomes. As a critical member of the team, you’ll identify opportunities for leveraging AI and ML to solve real-world problems, guiding efforts to mitigate risks, optimize resources, and improve lives.
Work with us to apply the power of AI and ML to solve scientific problems at the intersection of health and technology, and protect America from health, safety, and security threats.
What You’ll Work On:
Develop and optimize novel AI and ML algorithms tailored to scientific challenges, integrating domain knowledge to ensure results are actionable and relevant.
Design, validate, and deploy end-to-end machine learning and AI workflows in cloud environments to address complex analytical needs across the organization.
Collaborate with cross-functional teams to design efficient frameworks for data preparation, feature engineering, model selection, and outcome interpretation across data sources.
Build tools and infrastructure to enable seamless experimentation, rapid model iteration, and reproducibility of scientific AI and ML experiments.
Scale AI and ML solutions using advanced techniques such as distributed computing, cloud environments, including Azure, Databricks, and containerized deployments.
Implement automated pipelines for training, validating, and deploying models into production with rigorous monitoring and evaluation processes.
Develop containerized applications and APIs for exposing AI and ML model capabilities, ensuring accessibility and interpretability for stakeholders.
Identify and introduce state-of-the-art AI and ML techniques and tools such as explainable AI (XAI), reinforcement learning, and probabilistic modeling to enhance research outcomes and operational decision-making.
Support collaboration with data scientists, researchers, and engineers to bridge the gap between foundational AI and ML research and deployed, impactful applications.
Join us. The world can’t wait.
You Have:
4+ years of experience with Object-Oriented Programming (OOP)
3+ years of experience developing AI and ML models and solutions using distributed and cloud technologies, including Azure or Databricks
3+ years of experience developing, validating, and deploying scientific AI and ML workflows, including data preparation, model training, and model monitoring
Experience building containerized applications, including API design and secure authentication
Knowledge of AI and ML concepts, including supervised and unsupervised learning, statistical modeling, and deep learning methods
Ability to obtain and maintain a Public Trust or Suitability/Fitness determination based on client requirements
Bachelor’s degree in a Computer Science or Data Science field
Nice If You Have:
Experience with Python and PySpark
Experience with Azure Data Lake Services, Data Factory, Synapse, Purview, EntraID, or other cloud services
Experience with Kubernetes for managing containerized AI and ML workloads
Experience designing and implementing automated, reproducible data and ML pipelines in a cloud environment
Experience with version control tools, including Git
Knowledge of AI model explainability, ethical AI, or advanced deep learning frameworks such as TensorFlow or PyTorch
Master's degree in Computer Science, Machine Learning, or a related technical field
Vetting:
Applicants selected will be subject to a government investigation and may need to meet eligibility requirements of the U.S. government client.
Compensation
At Booz Allen, we celebrate your contributions, provide you with opportunities and choices, and support your total well-being. Our offerings include health, life, disability, financial, and retirement benefits, as well as paid leave, professional development, tuition assistance, work-life programs, and dependent care. Our recognition awards program acknowledges employees for exceptional performance and superior demonstration of our values. Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible to participate in Booz Allen’s benefit programs. Individuals that do not meet the threshold are only eligible for select offerings, not inclusive of health benefits. We encourage you to learn more about our total benefits by visiting the Resource page on our Careers site and reviewing Our Employee Benefits page.
Salary at Booz Allen is determined by various factors, including but not limited to location, the individual’s particular combination of education, knowledge, skills, competencies, and experience, as well as contract-specific affordability and organizational requirements. The projected compensation range for this position is $77,600.00 to $176,000.00 (annualized USD). The estimate displayed represents the typical salary range for this position and is just one component of Booz Allen’s total compensation package for employees. This posting will close within 90 days from the Posting Date.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
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.