Senior Machine Learning/Data Science Research Engineer

$146,000 - $234,000/Yr

Peraton - Silver Spring, MD

Full-time - Senior

Silver Spring, MD

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

About the position

The Senior Machine Learning/Data Science Research Engineer at Peraton is responsible for designing and implementing deep learning solutions specifically for network and graph representation learning. This role involves understanding user needs, developing machine learning models, and creating efficient data pipelines to support large-scale datasets. The engineer will leverage advanced machine learning techniques and frameworks to address complex challenges in cybersecurity and data analysis.

Responsibilities

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

Requirements

• Minimum of 8 years with BS/BA; Minimum of 6 years with MS/MA; Minimum of 3 years with PhD.
• Experience training conventional models from scratch (e.g., ordinary least squares (OLM), random forests, support vector machines (SVM), boosting methods, etc.).
• Personally trained a deep neural network (DNN): either trained a DNN from scratch OR leveraged transfer learning techniques to further tune a pretrained DNN to a specific target domain.
• Developed data wrangling/ETL transforms using python Pandas package.
• Experience with Git version control.

Nice-to-haves

• Experience training a deep neural network from scratch.
• Experience finding white-papers applicable to 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 (e.g., knowledge of OSI/TCP/IP models, network infrastructure).
• Experience developing on GNU/Linux-based operating system.
• Experience with MLOps tooling/workflows.
• Experience using containers (e.g., docker).
• Experience with orchestration solutions, including Docker Swarm, Kubernetes, Terraform.
• Top Secret Clearance.

Benefits

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