Lead Machine Learning/Data Science Research Engineer

$146,000 - $234,000/Yr

Peraton - Silver Spring, MD

Full-time

Silver Spring, MD

Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services

About the position

The Machine Learning/Data Science Research Engineer at Peraton Labs will engage in the design and implementation of deep learning solutions specifically for network/graph representation learning. This role involves understanding user needs to drive performance and infrastructure requirements, converting these needs into user interface requirements, and applying CI/CD best practices to scale ML solutions. The position is critical in advancing cybersecurity research and protecting national cyber infrastructure.

Responsibilities

• Frame the problem and research current state-of-the-art ML solutions to assess their suitability.
• Leverage deep learning frameworks (e.g., PyTorch, Tensorflow) to develop tailored deep learning solutions.
• Develop extract-transform-load (ETL) pipelines to curate large-scale ML datasets.
• Utilize graph neural networks (GNN) to construct embedded/latent representations for downstream tasks.
• Train ML models using automated hyper-parameter tuning frameworks.
• Design data models to capture real-world phenomena using graph data structures efficiently.

Requirements

• Minimum of 8 years of experience with a BS/BA; 6 years with MS/MA; 3 years with PhD.
• Minimum of 2 years of team lead experience.
• Experience training conventional models from scratch (e.g., OLM, random forests, SVM, boosting methods).
• Experience personally training a deep neural network (DNN) from scratch or using transfer learning techniques.
• Developed data wrangling/ETL transforms using Python Pandas package.
• Experience with Git version control.
• US Citizenship and Top Secret clearance with the ability to obtain SCI.

Nice-to-haves

• Experience training a deep neural network from scratch.
• Experience finding white papers applicable to the problem area and tailoring provided code to application domains.
• Experience with Generative Modeling (e.g., GANs).
• Experience with Reinforcement Learning (RL) solutions.
• Network engineering experience (knowledge of OSI/TCP/IP models, network infrastructure).
• Experience developing on GNU/Linux-based operating systems.
• Experience with MLOps tooling/workflows.
• Experience using containers (e.g., Docker).
• Experience with orchestration solutions, including Docker Swarm, Kubernetes, Terraform.

Benefits

• Competitive salary range of $146,000 - $234,000 based on experience and other factors.