Machine Learning Engineer/Scientist

Precise Systems is seeking a Machine Learning Engineer/Scientist to support chemical and biological defense projects from its Edgewood, MD onsite location. In this role, you will apply machine learning and data science to biological and chemical datasets, connect predictive outputs to laboratory automation workflows, and help ensure models are ready for real-world laboratory use.

You will work under the direction of senior professionals across the full model lifecycle, from research and development through testing, verification, and evaluation. The position also includes building dashboards or graphical interfaces and integrating secure, lab-ready data pipelines using DevSecOps and MLOps practices.

• Location: Edgewood, MD (onsite)
• Salary: USD 76,709 - 115,064 per year
• Minimum experience: 3 years
• Role focus: Machine learning for chemical and biological datasets, with predictive metrics integrated into lab automation workflows

Responsibilities

• Perform research, development, testing, and evaluation of machine learning models for chemical and biological datasets.
• Contribute to chemical and biological R&D efforts aimed at advancing innovation and addressing emerging threats.
• Collaborate with interdisciplinary teams to develop machine learning solutions for biological and chemical challenges.
• Develop and apply state-of-the-art ML tools and algorithms to optimize DoD research efforts.
• Carry out internal verification and validation of models and code to support deployments for real laboratory use.
• Develop and implement dashboards or other graphical user interfaces that support laboratory automation for experimentation.
• Analyze biological or chemical data using Python and R to derive mathematical insights and improve system performance.
• Use DevSecOps and MLOps to integrate machine learning processes into secure data pipelines for laboratory use.
• Collaborate with academic and industry partners to test and refine algorithms and biological systems across diverse environments.
• Conduct ongoing research to keep models and analysis current with the latest advancements.

Requirements

• Education: Master’s degree in Computer Science, Computer Engineering, Computational Biology, or Bioinformatics (or Bachelor’s degree in a relevant field, as described)
• Experience (degree flexibility): OR Bachelor’s degree in a relevant field with 5 years of experience in a laboratory and/or computational environment.
• Experience (baseline): 3 years of experience in a laboratory and/or computational environment.
• Hands-on experience applying machine learning algorithms and data science techniques to physical science problems.
• Proficiency in Python and other programming languages commonly used in ML and data analysis.
• Familiarity with physical science and laboratory experience.
• Proficiency with software development approaches including agile, git, DevSecOps, and/or MLOps.
• Advanced communication skills for working with interdisciplinary teams, government representatives, and industry partners.
• Willingness to learn new technologies and take on new challenges.
• Strong written and oral communication skills, excellent interpersonal skills, and proficiency in PC software packages for data analysis and visualization.

Technologies

• Python
• R
• DevSecOPs, DevSecOps
• MLOps
• git
• agile
• TensorFlow
• PyTorch
• PC software packages

Benefits

• Health insurance
• Life and accidental death and dismemberment coverage
• Disability insurance
• Retirement plans
• Holiday pay
• Employee-managed leave
• Professional growth opportunities

Preferred Education

• Ph.D. in Computational Biology/Chemistry, Machine Learning, Physical Sciences, or a related field with 1 year of experience in a laboratory and/or computational environment.

Preferred Experience

• Expertise in advanced machine learning frameworks (e.g., TensorFlow, PyTorch) and their application to biological data.
• Experience with bioinformatics tools and databases.
• Experience performing wet laboratory experimentation to validate software and models.
• Knowledge of automation systems and robotics for laboratory workflows.
• Collaboration with academic and industry partners on synthetic biology and machine learning projects.

Compensation

Compensation at Precise Systems is determined by factors including education, experience, skills, competencies, and contract-specific requirements. The salary range for this position is $76,709.46 - $115,064.18 (annualized USD). This range represents the standard pay for the role and is one component of Precise Systems’ total compensation package.