Leidos Security Enterprise Solutions (SES) operation is seeking a Machine Learning Engineer with a strong analytical chemistry instrumentation background to support our data science and AI initiatives. You will help build and maintain ML models and pipelines collaborate with cross-functional teams and contribute to deploying scalable machine learning solutions in production. You will be developing new capabilities and intellectual property relating to our trace detection product line. Were building intelligent systems that drive real-world impact pushing the limits of what is possible with regards to automated security solutions and were looking for passionate curious and collaborative individuals to join our team.
Primary Responsibilities:
- Lead design development testing and deployment of machine learning models specific to Leidos trace detection algorithms based on Ion Mobility Spectrometry technology.
- Work with large datasets: cleaning preprocessing feature engineering.
- Collaborate with chemists data scientists engineers and product managers to integrate ML models into applications.
- Help monitor model performance and retrain/update models as needed.
- Contribute to documentation and best practices.
- Stay up to date with the latest ML research tools and technologies.
Requirements:
- Bachelors degree in chemistry or chemical engineering with 5 or more years of hands-on experience using Ion Mobility Spectrometry (IMS) or Mass Spectrometry (MS) systems. May also consider a degree in Computer Science Engineering Mathematics (or a related field) and 5 years of work experience using IMS or MS.
- Must have the ability to obtain a Public Trust clearance (US citizenship required).
- Solid understanding of machine learning fundamentals (e.g. supervised/ unsupervised learning model evaluation).
- Proficiency in Python and common ML libraries (e.g. scikit-learn pandas NumPy).
- Proficiency in Object-oriented software design.
- Familiarity with PyTorch or similar frameworks.
- Familiarity with cloud platforms (e.g. AWS GCP or Azure).
- Experience with version control tools (e.g. Git).
- Exposure to MLOps concepts or tools (e.g. MLflow Docker CI/CD).
- Basic knowledge of SQL and data querying.
- Strong problem-solving and communication skills.
- Eagerness to learn and adapt in a fast-paced environment.
Preferred Qualifications:
- Masters degree in chemistry/analytical chemistry/data science-related field and 35 years of hands-on experience in a machine learning or data science role (including internships research or full-time industry experience).
- Proven experience building validating and deploying machine learning models in real-world scenarios.
- Completed academic or industry projects that demonstrate the application of ML techniques to solve complex problems related to spectrometry-based instrumentation.
- Cloud platform certifications such as: Microsoft Certified: Azure AI Engineer Associate AWS Certified Machine Learning Specialty Google Cloud Professional Machine Learning Engineer.
- Experience using MLOps tools and workflows including MLflow Docker CI/CD pipelines and model monitoring.
- Familiarity with deep learning frameworks especially PyTorch and the ability to build and fine-tune neural network models.
- Exposure to data engineering workflows such as data pipelines (e.g. Airflow) distributed processing (e.g. Spark) or data lake architectures.
- Strong documentation skills and the ability to clearly communicate technical details to both technical and non-technical audiences.
- Contributions to open-source ML projects participation in Kaggle competitions or relevant publications (a plus).
If youre looking for comfort keep scrolling. At Leidos we outthink outbuild and outpace the status quo because the mission demands it. Were not hiring followers. Were recruiting the ones who disrupt provoke and refuse to fail. Step 10 is ancient history. Were already at step 30 and moving faster than anyone else dares.
Original Posting:
January 23 2026
For 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 $87100.00 - $157450.00
The Leidos pay range for this job level is a general guideline onlyand 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.
Required Experience:
IC
Leidos Security Enterprise Solutions (SES) operation is seeking a Machine Learning Engineer with a strong analytical chemistry instrumentation background to support our data science and AI initiatives. You will help build and maintain ML models and pipelines collaborate with cross-functional teams a...
Leidos Security Enterprise Solutions (SES) operation is seeking a Machine Learning Engineer with a strong analytical chemistry instrumentation background to support our data science and AI initiatives. You will help build and maintain ML models and pipelines collaborate with cross-functional teams and contribute to deploying scalable machine learning solutions in production. You will be developing new capabilities and intellectual property relating to our trace detection product line. Were building intelligent systems that drive real-world impact pushing the limits of what is possible with regards to automated security solutions and were looking for passionate curious and collaborative individuals to join our team.
Primary Responsibilities:
- Lead design development testing and deployment of machine learning models specific to Leidos trace detection algorithms based on Ion Mobility Spectrometry technology.
- Work with large datasets: cleaning preprocessing feature engineering.
- Collaborate with chemists data scientists engineers and product managers to integrate ML models into applications.
- Help monitor model performance and retrain/update models as needed.
- Contribute to documentation and best practices.
- Stay up to date with the latest ML research tools and technologies.
Requirements:
- Bachelors degree in chemistry or chemical engineering with 5 or more years of hands-on experience using Ion Mobility Spectrometry (IMS) or Mass Spectrometry (MS) systems. May also consider a degree in Computer Science Engineering Mathematics (or a related field) and 5 years of work experience using IMS or MS.
- Must have the ability to obtain a Public Trust clearance (US citizenship required).
- Solid understanding of machine learning fundamentals (e.g. supervised/ unsupervised learning model evaluation).
- Proficiency in Python and common ML libraries (e.g. scikit-learn pandas NumPy).
- Proficiency in Object-oriented software design.
- Familiarity with PyTorch or similar frameworks.
- Familiarity with cloud platforms (e.g. AWS GCP or Azure).
- Experience with version control tools (e.g. Git).
- Exposure to MLOps concepts or tools (e.g. MLflow Docker CI/CD).
- Basic knowledge of SQL and data querying.
- Strong problem-solving and communication skills.
- Eagerness to learn and adapt in a fast-paced environment.
Preferred Qualifications:
- Masters degree in chemistry/analytical chemistry/data science-related field and 35 years of hands-on experience in a machine learning or data science role (including internships research or full-time industry experience).
- Proven experience building validating and deploying machine learning models in real-world scenarios.
- Completed academic or industry projects that demonstrate the application of ML techniques to solve complex problems related to spectrometry-based instrumentation.
- Cloud platform certifications such as: Microsoft Certified: Azure AI Engineer Associate AWS Certified Machine Learning Specialty Google Cloud Professional Machine Learning Engineer.
- Experience using MLOps tools and workflows including MLflow Docker CI/CD pipelines and model monitoring.
- Familiarity with deep learning frameworks especially PyTorch and the ability to build and fine-tune neural network models.
- Exposure to data engineering workflows such as data pipelines (e.g. Airflow) distributed processing (e.g. Spark) or data lake architectures.
- Strong documentation skills and the ability to clearly communicate technical details to both technical and non-technical audiences.
- Contributions to open-source ML projects participation in Kaggle competitions or relevant publications (a plus).
If youre looking for comfort keep scrolling. At Leidos we outthink outbuild and outpace the status quo because the mission demands it. Were not hiring followers. Were recruiting the ones who disrupt provoke and refuse to fail. Step 10 is ancient history. Were already at step 30 and moving faster than anyone else dares.
Original Posting:
January 23 2026
For 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 $87100.00 - $157450.00
The Leidos pay range for this job level is a general guideline onlyand 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.
Required Experience:
IC
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