Machine Learning Engineer/Chemist jobs in United States
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Leidos · 10 hours ago

Machine Learning Engineer/Chemist

Leidos is a company focused on security enterprise solutions, seeking a Machine Learning Engineer with a strong analytical chemistry background to support data science and AI initiatives. The role involves building and maintaining machine learning models and pipelines, collaborating with cross-functional teams, and contributing to the deployment of scalable machine learning solutions in production.

ComputerGovernmentInformation ServicesInformation TechnologyNational SecuritySoftware
badNo H1BnoteSecurity Clearance RequirednoteU.S. Citizen Onlynote

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

Qualification

Ion Mobility SpectrometryMass SpectrometryMachine LearningPythonMLOpsCloud PlatformsObject-oriented DesignSQLEagerness to LearnProblem-solvingCommunication Skills

Required

Bachelor's 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

Master's degree in chemistry/analytical chemistry/data science-related field and 3–5 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)

Company

Leidos is a Fortune 500® innovation company rapidly addressing the world’s most vexing challenges in national security and health.

Funding

Current Stage
Public Company
Total Funding
unknown
2025-02-20Post Ipo Debt
2013-09-17IPO

Leadership Team

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James Carlini
Chief Technology Officer
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Theodore Tanner
Chief Technology Officer
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Company data provided by crunchbase