Machine Learning Engineer/Chemist

Leidos • Tewksbury, MA

15d

About The Position

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. We're building intelligent systems that drive real-world impact pushing the limits of what is possible with regards to automated security solutions, and we’re looking for passionate, curious, and collaborative individuals to join our team.

Requirements

• 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.

Nice To Haves

• 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).

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.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 11-50 employees