United States onlyAt Leidos, you'll contribute to AI solutions that serve critical national and global missions—ranging from defense and intelligence to healthcare, energy, and space exploration. Our work emphasizes Trusted Mission AI: systems that are transparent, ethical, resilient, and accountable. You’ll collaborate with multidisciplinary teams to transition AI research into operational environments where accuracy, security, and reliability are non-negotiable. Joining Leidos means applying your expertise to solve some of the most complex and meaningful challenges of our time.
We are looking for a motivated ML Software / AI data engineer who wants to work on challenging problems in a variety of domains – including enterprise IT, health, defense, intelligence, and energy – to get results that apply and go beyond the state of the art for measurably better outcomes. We apply our knowledge, capabilities, and experience to develop and deploy Trusted Mission AI – AI that deserves to be trusted by system owners, end users, and the public – to be accurate, ethical, reliable, and adaptable. We are looking for an individual to work with a team to deliver secure data products for use by AI agents.
Primary Responsibilities.
- Work with a team of agentic AI scientists, agentic AI scientists, data scientists and data engineers on defining and creating scalable data processing pipelines to generate quality data for use by AI.
- Develop, operate, and maintain data architectures that support discovery and metadata tagging
- Design and implement data access controls to produce a data transformation pipeline that discovers, repairs, logs, and deploys quality data plus security policy metadata
- Analyze data provided to detect anomalies
- Work with a team to design, build, train, and evaluate machine learning models
- Communicate results and methods for solutions to internal and external stakeholders.
- Work within teams of AI/ML researchers and engineers using Agile development processes
Basic Qualifications.
- Bachelor's degree in Computer Science, Data Science or related field and over 4+ years of relevant experience, or a Masters with 2+ years experience. Additional experience may be considered in lieu of degree.
- Strong Python programming fundamentals
- Experience with data repositories and ETL techniques
- Good understanding of machine learning algorithms, tools and platforms
- Experience with AI/ML tools, such as common Python packages (e.g., scikit-learn, NumPy, Pandas)
- Experience with tabular data analysis using languages such as SQL, R, and/or Python
- Experience using generative AI and LLM-based tools
- Experience with statistical modeling and data analysis
- Experience applying data quality and data conditioning methods
- Understanding of transformers and foundation models
- Self-starter with high intellectual curiosity
- Great communication skills, able to explain model results to a non-technical audience
- Proficient in data exploration techniques and tools
Preferred Qualifications.
- Experience with data visualization libraries such as Plotly, Streamlit, and matplotlib.
- Experience with building LLM and other Generative AI applications.
- Willingness to learn new skills and platforms to support data analytics.
- Ability and willingness to obtain a Secret or Top Secret security clearance
At Leidos, we don’t want someone who "fits the mold"—we want someone who melts it down and builds something better. This is a role for the restless, the over-caffeinated, the ones who ask, “what’s next?” before the dust settles on “what’s now.”
If you’re already scheming step 20 while everyone else is still debating step 2… good. You’ll fit right in.
Original Posting:
August 29, 2025For U.S. Positions: While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above.
Pay Range:
Pay Range $85,150.00 - $153,925.00The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.
