Leidos · 12 hours ago
Machine Learning Engineer/Chemist
Tewksbury, MA
Full-time
Onsite
Senior Level
$87K/yr - $157K/yr
5+ years expLeidos is an industry and technology leader serving government and commercial customers with smarter, more efficient digital and mission innovations. They are seeking a Machine Learning Engineer with a strong analytical chemistry background to support their data science and AI initiatives, focusing on building and maintaining ML models and pipelines. The role involves collaborating with cross-functional teams and contributing to the deployment of scalable machine learning solutions in production.
ComputerGovernmentInformation ServicesInformation TechnologyNational SecuritySoftware
No H1B
U.S. Citizen Only
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
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)
Benefits
Health and Wellness programs
Income Protection
Paid Leave
Retirement
Company
Leidos
Leidos is a Fortune 500® innovation company rapidly addressing the world’s most vexing challenges in national security and health.
10001+ employees
Funding
Current Stage
Public CompanyTotal Funding
unknown2025-02-20Post Ipo Debt
2013-09-17IPO
Leadership Team
James Carlini
Chief Technology Officer
Theodore Tanner
Chief Technology Officer
Recent News
MarketScreener
2025-12-16
2025-12-16
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