Staff Data Engineer -- Applied Machine Learning

About Us

Red Cell Partners is an incubation firm building and investing in rapidly scalable technology-led companies that are bringing revolutionary advancements to market in three distinct practice areas: healthcare, cyber, and national security. United by a shared sense of duty and deep belief in the power of innovation, Red Cell is developing powerful tools and solutions to address our Nation’s most pressing problems. 

Staff Data Engineer – Applied Machine Learning. Apply data engineering, data analytics, data science, and quantitative analysis to develop and optimize machine learning (ML) systems. Train ML modules, design and implement training pipelines, customize and fine-tune ML models, and design feedback systems for continuous improvement. Select ML algorithms based on problems and data, utilize Python libraries for model development, and conduct A/B testing to compare and refine model performances. Work with cross-functional teams to understand requirements and translate into ML solutions. McLean, VA headquarters; telecommuting permitted. Requires quarterly travel within the US. Requires Bachelor’s degree or higher in Machine Learning, Computer Science, Industrial Engineering, Data Engineering, or closely related field, and at least two years of industry experience in data modeling and analytics. Experience must include building ML systems for deployment into production environments, developing custom data models and algorithms for data set applications, developing A/B testing frameworks, managing ML model training pipelines, analyzing model performance and data accuracy, predictive modeling, TensorFlow, PyTorch, and Python. Mail resumes to: Trase Systems, Inc., Attn: Joe Laws, 1800 Tysons Blvd, Suite 900, McLean VA 22102. Ref MS.TR.VT96.

We’re an Equal Opportunity Employer: You’ll receive consideration for employment without regard to race, sex, color, religion, sexual orientation, gender identity, national origin, protected veteran status, or on the basis of disability.