Machine Learning Engineer​/Scientist

As a solutions-based company, Precise Systems is focused on innovation in support of the warfighters and aligning our expertise to deliver the highest quality of service. Powered by our highly skilled workforce, we provide expert consultation on network and weapons systems acquisition programs, maintenance/modernization programs, and sustainment programs with solutions in Digital Transformation, Advanced Engineering, Physical Sciences Research, Platform Lifecycle Support, and Technical Services.

Since our establishment, we have demonstrated and perfected our ability to manage the customer's needs, no matter how complex - offering exceptional service and the Precise solution.

Precise Systems seeks a Machine Learning Engineer or Scientist with experience in the physical sciences to support innovative chemical and biological defense projects that integrate automation, and physical science principles. The selected candidate will apply their academic and practical knowledge, experience, and expertise to optimize biomanufacturing data pipelines and perform data analytics using data science principles. The role involves integrating predictive performance metrics into laboratory processes using pythonic dashboards, adapting metrics and models to project needs, and executing them in laboratory settings to achieve desired outcomes.

Under the guidance of senior professionals, the individual will perform tasks encompassing research, development, testing, and evaluation of machine learning models towards chemical and biological datasets. The candidate will contribute to advancing chemical and biological research and development that drives innovation to out‑pace emerging threats while simultaneously providing modern solutions.

• Collaborate with interdisciplinary teams to develop machine learning solutions for biomanufacturing challenges.
• Develop and apply state‑of‑the‑art machine learning (ML) tools and algorithms to optimize DoD research efforts.
• Perform internal verification and validation of models and code to ensure deployments for real laboratory use.
• Develop and implement dashboards or other graphical user interfaces for automation for laboratory experimentation.
• Analyze biological data using languages such as Python and R to derive mathematical insights and improve system performance.
• Employ Dev Sec Ops  and MLOps to integrate machine learning processes into secure data pipelines.
• Collaborate with academic and industry partners to test and refine algorithms and biological systems in diverse environments.
• Perform research to keep models and analysis up to date with the latest advancements.

• Master's degree in Computer Science, Computer Engineering, Computational Biology, Bioinformatics, or a related field with three (3) years of experience in a laboratory and/or computational environment.
• Or a Bachelor's degree in a relevant field with five (5) years of experience in a laboratory and/or computational environment.

• Ph.D. in Computational Biology, Machine Learning, or a related field with one (1) year 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 machine learning and data analysis.
• Familiarity with physical science and laboratory experience.
• Proficiency with software development approaches such as agile, git, Dev Sec Ops , and/or MLOps.
• Advanced communication skills for interacting 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.

• Expertise in advanced machine learning frameworks (e.g., Tensor Flow, PyTorch) and their application to biological data.
• Experience with bioinformatics tools and databases.
• Experience performing wet laboratory experimentation…